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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 [ 11 C]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 [ 11 C]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 [ 11 C]MeDAS PET quantification, due to high inter-subject variability. Consequently, when unbiased quantification of [ 11 C]MeDAS PET data is required, individual AIF needs to be used., (Copyright © 2022. Published by Elsevier Inc.)

Purpose: Multiple sclerosis (MS) is a disease characterized by inflammatory demyelinated lesions. New treatment strategies are being developed to stimulate myelin repair. Quantitative myelin imaging could facilitate these developments. This first-in-man study aimed to evaluate [ 11 C]MeDAS as a PET tracer for myelin imaging in humans., Methods: Six healthy controls and 11 MS patients underwent MRI and dynamic [ 11 C]MeDAS PET scanning with arterial sampling. Lesion detection and classification were performed on MRI. [ 11 C]MeDAS time-activity curves of brain regions and MS lesions were fitted with various compartment models for the identification of the best model to describe [ 11 C]MeDAS kinetics. Several simplified methods were compared to the optimal compartment model., Results: Visual analysis of the fits of [ 11 C]MeDAS time-activity curves showed no preference for irreversible (2T3k) or reversible (2T4k) two-tissue compartment model. Both volume of distribution and binding potential estimates showed a high degree of variability. As this was not the case for 2T3k-derived net influx rate (K i ), the 2T3k model was selected as the model of choice. Simplified methods, such as SUV and MLAIR2 correlated well with 2T3k-derived K i , but SUV showed subject-dependent bias when compared to 2T3k. Both the 2T3k model and the simplified methods were able to differentiate not only between gray and white matter, but also between lesions with different myelin densities., Conclusion: [ 11 C]MeDAS PET can be used for quantification of myelin density in MS patients and is able to distinguish differences in myelin density within MS lesions. The 2T3k model is the optimal compartment model and MLAIR2 is the best simplified method for quantification., Trial Registration: NL7262. Registered 18 September 2018., (© 2022. The Author(s).)

Objectives: Currently, multiple sclerosis is treated with anti-inflammatory therapies, but these treatments lack efficacy in progressive disease. New treatment strategies aim to repair myelin damage and efficacy evaluation of such new therapies would benefit from validated myelin imaging techniques. Several MRI methods for quantification of myelin density are available now. This systematic review aims to analyse the performance of these MRI methods., Methods: Studies comparing myelin quantification by MRI with histology, the current gold standard, or assessing reproducibility were retrieved from PubMed/MEDLINE and Embase (until December 2019). Included studies assessed both myelin histology and MRI quantitatively. Correlation or variance measurements were extracted from the studies. Non-parametric tests were used to analyse differences in study methodologies., Results: The search yielded 1348 unique articles. Twenty-two animal studies and 13 human studies correlated myelin MRI with histology. Eighteen clinical studies analysed the reproducibility. Overall bias risk was low or unclear. All MRI methods performed comparably, with a mean correlation between MRI and histology of R 2 =0.54 (SD=0.30) for animal studies, and R 2 =0.54 (SD=0.18) for human studies. Reproducibility for the MRI methods was good (ICC=0.75-0.93, R 2 =0.90-0.98, COV=1.3-27%), except for MTR (ICC=0.05-0.51)., Conclusions: Overall, MRI-based myelin imaging methods show a fairly good correlation with histology and a good reproducibility. However, the amount of validation data is too limited and the variability in performance between studies is too large to select the optimal MRI method for myelin quantification yet., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)