IEEE Transactions on Medical Imaging | 2019

Scan-Time Corrections for 80–100-min Standardizetd Uptake Volume Ratios to Measure the 18F-AV-1451 Tracer for Tau Imaging

 
 
 
 
 

Abstract


The <sup>18</sup>F-AV-1451 PET tracer binds to tau, an Alzheimer’s disease biomarker. The standardized uptake value ratio (SUVR) 80–100 min window is widely used to quantify tau binding, although <sup>18</sup>F-AV-1451 continues increasing relative to a reference region in regions with tau deposition. Left uncorrected, acquisition time inaccuracies can lead to errors from −4% to 6% in 20-min SUVR measurements in subjects with Alzheimer’s disease. In 40 subjects with scans from 75–115 min following <sup>18</sup>F-AV-1451 injection, we created 20-min reconstructions (<inline-formula> <tex-math notation= LaTeX >$4\\times 5$ </tex-math></inline-formula> min) of start-times ranging from 75–85 min, as proxies of offset scans and calculated the mean in regions of interest (ROIs). We developed a segmented least squares (SLS) method to obtain error-minimizing weighting coefficients for <sup>18</sup>F-AV-1451 ROIs that best predict SUVR 80–100 from weighted means of SUVRs from offset start-times. We compared residual errors of our SLS method to those in: 1) uncorrected offset 20-min-SUVRs; 2) the mean of five-min frames within the 80–100 window; and 3) a least-squares interpolation method. We evaluated errors induced by start-time offset on SUVRs for each method. The SLS, which corrected using least-squares coefficients of 5-min components, consistently reduced errors across all offset start-times. Effect size analysis for simulated clinical longitudinal <sup>18</sup>F-AV-1451 drug trials showed that uncorrected 20-min offset SUVRs would require up to 20% more participants to detect treatment effects compared with using SLS. Correction of SUVR scan-time errors by SLS minimizes errors compared with other correction methods and may be extended to other scanners and tracers.

Volume 38
Pages 697-709
DOI 10.1109/TMI.2018.2870441
Language English
Journal IEEE Transactions on Medical Imaging

Full Text