Hi everyone, I was working with HABS data and I found out there is no centiloids values, only SUVr. As you may know, these values can be converted, and as I read in the ImageDataRelease document: "**Pittsburgh Compound B (PiB – amyloid beta): **PiB data was collected as a full dynamic sequence from 0-60 minutes post injection and is reconstructed in 39 frames (8x15 seconds, 4 by 60 seconds, 27 x 120 seconds). Timing information (onset and duration in seconds) for each frame is provided. We have also created a 40-60 minute dataset for those who are only interested in generating SUVR and not DVR measures. The files for SUVR are the last 10 frames of the full dynamic sequence covering the 40-60 minute post injection time frame. Note that many SUVR PiB protocols are from 50-70 minutes post injection, so expect a small but consistent offset if you are comparing HABS SUVR PiB data to other 50-70 minute PiB SUVR data. You can use the GAAIN Centiloid dataset as a reference (full dynamic data from 0 to 70 minutes post injection) to compute the same measure for 40-60 and 50-70 in order to generate a linear transform for merging data. The 40-60 and 50-70 should be highly collinear with small offsets. Using one of our own pipelines for the FLR composite we computed the linear mapping as (1.0366•X)-0.0265 to map 40-60 measures to the 50-70 scale. The 40-60 dataset is approximately 13 gigabytes in size, and the full dynamic dataset is approximately 50 gigabytes in size. There is a small set (18 scans) of the dynamic images that are missing either the first or second frame post injection due to inadequate count statistics. The timing information makes these cases transparent and should not notably affect dynamic modeling." And I was wondering if the steps are the following or I should do something else in order to convert the data: 1) Adjust SUVr column with the formula **(1.0366•X)-0.0265** and 2) Use GAAIN PiB centiloid equation to convert the resulting column into centilods. Is this the right path? Does anyone know another one? Thanks.