WE-H-207A-03: The Universality of the Lognormal Behavior of [F-18]FLT PET SUV Measurements

Purpose: Log transforming [F-18]FDG PET standardized uptake values (SUVs) has been shown to lead to normal SUV distributions, which allows utilization of powerful parametric statistical models. This study identified the optimal transformation leading to normally distributed [F-18]FLT PET SUVs from s...

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Bibliographic Details
Published in:Medical physics (Lancaster) 2016-06, Vol.43 (6), p.3845-3846
Main Authors: Scarpelli, M, Eickhoff, J, Perlman, S, Jeraj, R
Format: Article
Language:English
Subjects:
60 APPLIED LIFE SCIENCES
BIOLOGICAL MARKERS
BIOMEDICAL RADIOGRAPHY
Calibration
Cancer
CAT SCANNING
Collective models
DISTRIBUTION
FLUORINE 18
Image analysis
POSITRON COMPUTED TOMOGRAPHY
Positron emission tomography
RADIATION PROTECTION AND DOSIMETRY
RADIOLOGY AND NUCLEAR MEDICINE
Statistical model calculations
STATISTICAL MODELS
TRANSFORMATIONS
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Summary:Purpose: Log transforming [F-18]FDG PET standardized uptake values (SUVs) has been shown to lead to normal SUV distributions, which allows utilization of powerful parametric statistical models. This study identified the optimal transformation leading to normally distributed [F-18]FLT PET SUVs from solid tumors and offers an example of how normal distributions permits analysis of non-independent/correlated measurements. Methods: Forty patients with various metastatic diseases underwent up to six FLT PET/CT scans during treatment. Tumors were identified by nuclear medicine physician and manually segmented. Average uptake was extracted for each patient giving a global SUVmean (gSUVmean) for each scan. The Shapiro-Wilk test was used to test distribution normality. One parameter Box-Cox transformations were applied to each of the six gSUVmean distributions and the optimal transformation was found by selecting the parameter that maximized the Shapiro-Wilk test statistic. The relationship between gSUVmean and a serum biomarker (VEGF) collected at imaging timepoints was determined using a linear mixed effects model (LMEM), which accounted for correlated/non-independent measurements from the same individual. Results: Untransformed gSUVmean distributions were found to be significantly non-normal (p0.10 for all timepoints). Log transformed data were incorporated into the LMEM. VEGF serum levels significantly correlated with gSUVmean (p
ISSN:0094-2405
2473-4209
DOI:10.1118/1.4958008