So the CenTauR approach is basically, you know, the analog of the centiloid scale for amyloid PET. The idea is to harmonize tau PET quantification results across different radiotracers and quantification pipelines, right? So basically the approach we use is heavily inspired by the centiloid approach, though we apply a different statistical method called JPM for harmonization, right? We don’t rely on a single reference radio tracer, but instead we use all the available head-to-head data we have to derive linear conversion equations...
So the CenTauR approach is basically, you know, the analog of the centiloid scale for amyloid PET. The idea is to harmonize tau PET quantification results across different radiotracers and quantification pipelines, right? So basically the approach we use is heavily inspired by the centiloid approach, though we apply a different statistical method called JPM for harmonization, right? We don’t rely on a single reference radio tracer, but instead we use all the available head-to-head data we have to derive linear conversion equations. So the way it works eventually, it’s very similar to the centiloid scale, it’s just a linear transformation equation to convert SUVRs, acquired using what we call the standard method to the universal CenTauR scale. And the main advantage of the CenTauR scale is that it is independent in principle of the radio tracer and quantification pipeline. So we can establish reference values, cut points in multiple regions of interest so that we can, for instance, use a cut point that has been derived using a different radiotracer and a different quantification pipeline with another radiotracer and our own quantification pipeline. So that’s basically the main strength. So, yeah, we provide in this work, we provide the framework. We explain how to calibrate methods. We will provide as well the conversion equations. And on top of that, we perform a preliminary validation of the method basically by comparing the frequencies of tau PET positivity when defined using a universal CenTauR cutoff, right, in data sets scanned with different radio tracers that are matched based on clinical diagnosis age. So what we found was basically that the frequencies of tau PET positivity were remarkably consistent across the different matched data sets, which supports the idea that the CenTauR harmonization is doing a good job, right? And when compared to traditional approaches based on two standard deviations, based on defining cut points, based on two standard deviations over the mean of cognitively normal individuals, that’s a very commonly used approach in research, right? We see that the CenTauR method outperforms this commonly used approach. So we believe that, yeah, the method seems to be working and provides some value over the traditional approaches.
This transcript is AI-generated. While we strive for accuracy, please verify this copy with the video.
