Assessment of tumor response after chemotherapy using (18)F-FDG PET metrics is gaining acceptance. Several studies have suggested that the parameters metabolically active tumor volume (MTV) and total lesion glycolysis (TLG) are superior to SUVmax for measuring tumor burden. However, the measurement of MTV and TLG is still controversial; the most common method uses an absolute threshold of 42% of SUVmax Recently, we implemented a background-adaptive method to determine the background-subtracted lesion activity (BSL) and the background-subtracted volume (BSV). In this study, we investigated the correlation between such PET metrics and histopathologic response in non-small cell lung carcinoma (NSCLC).
Methods: Forty-four NSCLC patients were retrospectively identified. Their PET/CT data on both types of scan before and after neoadjuvant chemotherapy were analyzed regarding SUVmax, MTV, TLG, BSL, and BSV, as well as the relative changes in these parameters. The tumor regression score as an indicator of histopathologic response was scored on hematoxylin- and eosin-stained sections of the surgical specimens using a 4-tiered scale (scores 1-4). The correlation between score and the absolute and relative PET metrics after chemotherapy was analyzed using Spearman rank correlation tests.
Results: Tumors that demonstrated a good response after neoadjuvant chemotherapy had significantly lower (18)F-FDG activity than nonresponding tumors (scores 3 and 4: SUVmax, 4.2 [range, 1.8-7.9] vs. scores 1 and 2: SUVmax, 8.1 [range, 1.4-40.4]; P = 0.001). The same was found for change in SUVmax and score (P = 0.001). PET volume metrics based on a 42% fixed threshold for SUVmax did not correlate with score (TLG, P = 0.505; MTV, P = 0.386). However, both of the background activity-based PET volume metrics-BSL and BSV-significantly correlated with score (P < 0.001 each).
Conclusion: PET volume metrics based on background-adaptive methods correlate better with histopathologic tumor regression score in NSCLC patients under neoadjuvant chemotherapy than algorithms and methods using a fixed threshold (42% SUVmax).
Keywords: NSCLC; neoadjuvant therapy; quantification; tumor regression; volume segmentation.
© 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.