Harmonizing florbetapir and PiB PET measurements of cortical A β plaque burden using multiple regions-of-interest and machine learning techniques: An alternative to the Centiloid approach

DISCUSSION: ML improved mcAβ comparability. Additional studies are needed for the generalizability to other amyloid tracers, and to tau PET. Highlights Centiloid is a calibration of the amyloid scale, not harmonization. Centiloid unifies the amyloid scale without improving inter-tracer association (R2 ). Machine learning (ML) can harmonize the amyloid scale by improving R2 . ML harmonization maps multi-regional florbetapir SUVRs to PiB mean-cortical SUVR. Artificial neural network ML increases Centiloid R2 from 86% to 97%.PMID:38276892 | DOI:10.1002/alz.13677
Source: The Journal of Alzheimers Association - Category: Psychiatry Authors: Source Type: research