Investigation of image-derived input functions for non-invasive quantification of myelin density using [11C]MeDAS PET

Chris W J van der Weijden; Anouk van der Hoorn; Yanming Wang; Antoon T M Willemsen; Rudi A J O Dierckx; Adriaan A Lammertsma; Erik F J de Vries

doi:10.1016/j.neuroimage.2022.119772

Investigation of image-derived input functions for non-invasive quantification of myelin density using [¹¹C]MeDAS PET

Neuroimage. 2022 Dec 1:264:119772. doi: 10.1016/j.neuroimage.2022.119772. Epub 2022 Nov 24.

Authors

Chris W J van der Weijden¹, Anouk van der Hoorn², Yanming Wang³, Antoon T M Willemsen¹, Rudi A J O Dierckx¹, Adriaan A Lammertsma¹, Erik F J de Vries⁴

Affiliations

¹ Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen 9713GZ, the Netherlands.
² Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen 9713GZ, the Netherlands.
³ Department of Radiology, Case Western Reserve University, Cleveland, OH 44106, United States.
⁴ Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen 9713GZ, the Netherlands. Electronic address: e.f.j.de.vries@umcg.nl.

PMID: 36436711
DOI: 10.1016/j.neuroimage.2022.119772

Abstract

Multiple sclerosis (MS) is an inflammatory demyelinating disease. Current treatments are focussed on immune suppression to modulate pathogenic activity that causes myelin damage. New treatment strategies are needed to prevent demyelination and promote remyelination. Development of such myelin repair therapies require a sensitive and specific biomarker for efficacy evaluation. Recently, it has been shown that quantification of myelin density is possible using [¹¹C]MeDAS PET. This method, however, requires arterial blood sampling to generate an arterial input function (AIF). As the invasive nature of arterial sampling will reduce clinical applicability, the purpose of this study was to assess whether an image-derived input function (IDIF) can be used as an alternative way to facilitate its routine clinical use. Six healthy controls and 11 MS patients underwent MRI and [¹¹C]MeDAS PET with arterial blood sampling. The application of both population-based whole blood-to-plasma conversion and metabolite corrections were assessed for the AIF. Next, summed images of the early time frames (0-70 s) and the frame with the highest blood-brain contrast were used to generate IDIFs. IDIFs were created using either the hottest 2, 4, 6 or 12 voxels, or an isocontour of the hottest 10% voxels of the carotid artery. This was followed by blood-to-plasma conversion and metabolite correction of the IDIF. The application of a population-based metabolite correction of the AIF resulted in high correlations of tracer binding (K_i) within subjects, but variable bias across subjects. All IDIFs had a sharper and higher peak in the blood curves than the AIF, most likely due to dispersion during blood sampling. All IDIF methods resulted in similar high correlations within subjects (r = 0.95-0.98), but highly variable bias across subjects (mean slope=0.90-1.09). Therefore, both the use of population based blood-plasma and metabolite corrections and the generation of the image-derived whole-blood curve resulted in substantial bias in [¹¹C]MeDAS PET quantification, due to high inter-subject variability. Consequently, when unbiased quantification of [¹¹C]MeDAS PET data is required, individual AIF needs to be used.

Keywords: Demyelination; Image-derived input function; Multiple sclerosis; Positron emission tomography; Quantitative myelin imaging.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Arteries
Humans
Magnetic Resonance Imaging
Multiple Sclerosis* / diagnostic imaging
Myelin Sheath
Positron-Emission Tomography* / methods