Translating SUVR bias correction to amyloid PET enables early imaging and more accurate simplified quantification
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Introduction
A new method that corrects for time-dependent bias in standardized-uptake value ratios (SUVRs) was adapted and optimized for [ 11 C]PiB (PiB) amyloid-beta (Aβ) PET, across low-to-high Aβ loads, relying only on PET data collected during the SUVR time-window. This modeling approach was evaluated in cross-sectional and longitudinal cohorts for earlier and shorter SUVR time-windows (30-45 min, 45-60 min) than commonly applied, to enable higher throughput imaging.
Methods
The SUVR correction ( SUVR c) approach was optimized and tested on separate cross-sectional (n=88), and longitudinal (36 participants, two time-points, 72 images) cohorts from the Harvard Aging Brain Study. The cross-sectional cohort spanned low, intermediate and high levels of cortical Aβ pathology and the longitudinal images included two cohorts with low (5-10%) and high levels (~40%) of Aβ change. SUVR and SUVR c were compared against SRTM DVR (0-60 min) to quantify Aβ burden through Pearson’s and Lin’s correlations, difference plots and longitudinal change.
Results
The mean regional bias in PiB SUVR (5-15%, depending on time-window and Aβ burden) was significantly reduced to < 3% by SUVR c (corrected p < 0.05) in the cross-sectional cohorts for all time-windows, along with reductions in bias variability. SUVR c also showed higher Pearson’s correlation (r) and Lin’s concordance (LCC) with DVR across time-windows (r=0.98, LCC=0.99 at 30-45 min and 45-60 min) compared to uncorrected SUVR (r=0.96, LCC=0.95 at 30-45 min, r=0.97, LCC=0.92 at 45-60 min). Bland-Altman plots confirmed better agreement between SUVR c and DVR (mean bias at 30-45 min: 0.02 for SUVR c, 0.10 for SUVR ; mean bias at 45-60 min: 0.01 for SUVR c, 0.17 for SUVR ). Longitudinal DVR changes were more accurately represented by SUVR c, compared to uncorrected SUVR .
Conclusions
SUVR c for [ 11 C]PiB PET enables more accurate quantification of Aβ burden than SUVR in cross-sectional and longitudinal studies (relative to SRTM DVR), while enabling imaging at earlier and shorter time-windows. The improved accuracy would be beneficial in better quantifying amyloid re-emergence post anti-amyloid therapy and could be used for kinetic harmonization across time-windows and radiotracers.
