Chemotherapy response evaluation with 18F-FDG PET in patients with non-small cell lung cancer.

UNLABELLED: The aim of this prospective study was to evaluate the value of (18)F-FDG PET for the assessment of chemotherapy response in patients with non-small cell lung cancer. Furthermore, part of the objective of this study was to compare 2 methods to quantify changes in glucose metabolism. METHODS: In 51 patients, dynamic (18)F-FDG PET was performed before and at 5-8 wk into treatment. Simplified methods to measure glucose metabolism (standardized uptake value [SUV]) and quantitative measures (metabolic rate of glucose [MR(Glu)]), derived from Patlak analysis, were evaluated. The overall survival and progression-free survival with respect to MR(Glu) and SUV were calculated using Kaplan-Meier estimates. Fractional changes in tumor glucose use were stratified by the median value and also the predefined EORTC (European Organization for Research and Treatment of Cancer) metabolic response criteria, and criteria applying cutoff levels similar to those of RECIST (Response Evaluation Criteria in Solid Tumors) were evaluated. RESULTS: When stratifying at the median value of DeltaMR(Glu) and DeltaSUV, the difference in overall survival (P = 0.017 for DeltaMR(Glu), P = 0.018 for DeltaSUV) and progression-free survival (P = 0.002 for DeltaMR(Glu), P = 0.0009 for DeltaSUV) was highly significant. When applying the predefined criteria for metabolic response, the cutoff levels as also used for size measurement (RECIST) showed significant differences for DeltaSUV between response categories in progression-free survival (P = 0.0003) as well as overall survival (P = 0.027). CONCLUSION: The degree of chemotherapy-induced changes in tumor glucose metabolism as determined by (18)F-FDG PET is highly predictive for patient outcome, stratifying patients into groups with widely differing overall survival and progression-free survival probabilities. The use of (18)F-FDG PET for therapy monitoring seems clinically feasible, because simplified methods to measure tumor glucose use (SUV) are sufficiently reliable and can replace more complex, quantitative measures (MR(Glu)) in this patient population.

Comparison of image-derived and arterial input functions for estimating the rate of glucose metabolism in therapy-monitoring 18F-FDG PET studies.

UNLABELLED: The use of dynamic (18)F-FDG PET to determine changes in tumor metabolism requires tumor and plasma time-activity curves. Because arterial sampling is invasive and laborious, our aim was to validate noninvasive image-derived input functions (IDIFs). METHODS: We obtained 136 dynamic (18)F-FDG PET scans of 76 oncologic patients. IDIFs were determined using volumes of interest over the left ventricle, ascending aorta, and abdominal aorta. The tumor metabolic rate of glucose (MRGlu) was determined with the Patlak analysis, using arterial plasma time-activity curves and IDIFs. RESULTS: MRGlu using all 3 IDIFs showed a high correlation with MRGlu based on arterial sampling. Comparability between the measures was also high, with the intraclass correlation coefficient being 0.98 (95% confidence interval, 0.97-0.99) for the ascending aorta IDIF, 0.94 (0.92-0.96) for the left ventricle IDIF, and 0.96 (0.93-0.98) for the abdominal aorta IDIF. CONCLUSION: The use of IDIFs is accurate and simple and represents a clinically viable alternative to arterial blood sampling.