PURPOSE: To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. MATERIALS AND METHODS: Ten canine sinonasal cancer patients underwent PET/CT scans of [(18)F]FDG (FDG(pre)), [(18)F]FLT (FLT(pre)), and [(61)Cu]Cu-ATSM (Cu-ATSM(pre)). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at 3 months (FDG(post)). Regression of standardized uptake values in baseline FDG(pre), FLT(pre) and Cu-ATSM(pre) tumour voxels to those in FDG(post) images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R(2). Hypothesis testing of coefficients over the patient population was performed. RESULTS: Multivariate linear model fits of FDG(pre) to FDG(post) were significantly positive over the population (FDG(post) ~ 0.17 · FDG(pre), p = 0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p = 0.01). Generalized-linear model fits related FDG(pre) to FDG(post) by a linear power law (FDG(post) ~ FDG(pre)(0.93),p<0.001). Univariate mixture model fits of FDG(pre) improved R(2) from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. CONCLUSIONS: Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent.
PURPOSE: To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. MATERIALS AND METHODS: Ten canine sinonasal cancerpatients underwent PET/CT scans of [(18)F]FDG (FDG(pre)), [(18)F]FLT (FLT(pre)), and [(61)Cu]Cu-ATSM (Cu-ATSM(pre)). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at 3 months (FDG(post)). Regression of standardized uptake values in baseline FDG(pre), FLT(pre) and Cu-ATSM(pre) tumour voxels to those in FDG(post) images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R(2). Hypothesis testing of coefficients over the patient population was performed. RESULTS: Multivariate linear model fits of FDG(pre) to FDG(post) were significantly positive over the population (FDG(post) ~ 0.17 · FDG(pre), p = 0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p = 0.01). Generalized-linear model fits related FDG(pre) to FDG(post) by a linear power law (FDG(post) ~ FDG(pre)(0.93),p<0.001). Univariate mixture model fits of FDG(pre) improved R(2) from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. CONCLUSIONS: Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent.
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