Source
King's College London, Osteoporosis Screening and Research Unit, Guy's Hospital, London, UK. muhammed.siddique@kcl.ac.uk
Abstract
The planning of research studies requires an understanding of the minimum number of subjects required. The aim of this study was to evaluate different methods of analyzing (18)F-fluoride PET ((18)F(-) PET) dynamic spine scans to find the approach that requires the smallest sample size to detect a statistically significant response to treatment.
METHODS:
Eight different approaches to (18)F(-) PET analysis (3 variants of the Hawkins 3-tissue compartmental model, 3 variants of spectral analysis, deconvolution, and Patlak analysis) were used to evaluate the fluoride plasma clearance to bone mineral (K(i)). Standardized uptake values (SUVs) were also studied. Data for 20 women who had (18)F(-) PET spine scans at 0, 6, and 12 mo after stopping long-term bisphosphonate treatment were used to compare precision errors. Data for 18 women who had scans at baseline and 6 mo after starting teriparatide treatment were used to compare response to treatment.
RESULTS:
The 4 approaches that fitted the rate constant k(4) describing the reverse flow of (18)F from bone as a free variable showed close agreement in K(i) values, with correlation coefficients greater than 0.97. Their %CVs were 14.4%-14.8%, and treatment response to teriparatide was 23.2%-23.8%. The 3 methods that assumed k(4) = 0 gave K(i) values 20%-25% lower than the other methods, with correlation coefficients of 0.83-0.94, percentage coefficients of variation (%CVs) of 12.9%-13.3%, and treatment response of 25.2%-28.3%. A Hawkins model with k(4) = 0.01 min(-1) did not perform any better (%CV, 14.2%; treatment response, 26.1%). Correlation coefficients between SUV and the different K(i) methods varied between 0.60 and 0.65. Although SUV gave the best precision (%CV, 10.1%), the treatment response (3.1%) was not statistically significant.
CONCLUSION:
Methods that calculated K(i) assuming k(4) = 0 required fewer subjects to demonstrate a statistically significant response to treatment than methods that fitted k(4) as a free variable. Although SUV gave the smallest precision error, the absence of any significant changes make it unsuitable for examining response to treatment in this study.