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Abstract
BACKGROUND:
To identify whether early metabolic responses as determined using 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) during radiotherapy (RT) predict outcomes in patients with esophageal cancer.

METHODS:
Twenty-one patients with esophageal cancer who received pre-treatment 18F-FDG PET/CT (PET1) and inter-fractional 18F-FDG PET/CT (PET2) after 11 fractions of RT (median 23.1 Gy, 2.1 Gy per fraction) were retrospectively reviewed. The region of interest for each calculation was delineated using "PET Edge". We calculated PET parameters including maximum and mean standardized uptake values (SUVmax and SUVmean, respectively), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). The relative changes (%) were calculated using the logarithmically transformed parameter values for the PET1 and PET2 scans. Multivariate analysis of locoregional recurrence and distant failures were performed using Cox regression analysis. After identifying statistically significant PET parameters for discriminating responders from non-responders, receiver operating characteristics curve analyses were used to assess the potentials of the studied PET parameters.

RESULTS:
After a median follow-up of 13 months, the 1-year overall and progression-free survival rates were 79.0% and 34.4%, respectively. Four patients developed locoregional recurrences (LRRs) and 8 had distant metastases (DMs). The 1-year overall LRR-free rate was 76.9% while the DM-free rate was 60.6%. The relative changes in MTV (ΔMTV) were significantly associated with LRR (p = 0.03). Conversely, the relative changes in SUVmean (ΔSUVmean) were associated with the risk of DM (p = 0.02). An ΔMTV threshold of 1.14 yielded a sensitivity of 60%, specificity of 94%, and an accuracy of 86% for predicting an LRR. Additionally, a ΔSUVmean threshold of a 35% decrease yielded a sensitivity of 67%, specificity of 83%, and accuracy of 76% for the prediction DM.

TRIAL REGISTRATION:
Retrospectively registered.

CONCLUSIONS:
Changes in tumor metabolism during RT could be used to predict treatment responses, recurrences, and prognoses in patients with esophageal cancer.

Author information

Kim N1, Cho H2, Yun M2, Park KR3, Lee CG4.
1
Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea.
2
Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
3
Department of Radiation Oncology, Kosin University Gospel Hospital, Busan, Republic of Korea.
4
Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Republic of Korea. CGLEE1023@yuhs.ac.