Abstract
This study explored the value of serial 18-fludeoxyglucose-positron emission tomography (18F-FDG-PET/CT) in predicting disease-free survival (DFS) in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiation (NCRT) and surgery. We prospectively studied 46 patients with LARC who underwent NCRT and surgery. 18F-FDG-PET/CT scans were performed at three time-points before surgery (pre-NCRT-PET1, during NCRT-PET2 and following completion of NCRT-PET3). The following semi-quantitative PET parameters were analysed at each time point: maximum standardized uptake value (SUVmax), SUVmean, metabolic tumour volume (MTV) and tumour lesion glycolysis (TLG). Absolute and percentage changes in these parameters were analysed between time points. Statistical analysis consisted of median tests, Cox regression and Kaplan-Meier analysis for DFS. The median follow-up time was 24 months. A reduction in PET parameters showed statistically significant differences for patients with recurrence compared to those without; percentage changes in MTV between PET1 and PET3 (cut-off: 87%, p = 0.023), percentage changes in TLG between PET1 and PET3 (cut-off: 94%, p = 0.02) and absolute change in MTV PET1 and PET2 (cut-off: 10.25, p = 0.001).An absolute reduction in MTV between PET1 and PET3 (p=0.013), a percentage reduction in TLG between PET1 and PET2 (p=0.021), SUVmax and SUVmean at PET2 (p = 0.01, p = 0.027 respectively)were also prognostic indicators of recurrence.MTV percentage change between PET1 and PET2 and SUVmean percentage change between PET1 and PET3 were also trending towards significance (p = 0.052, p = 0.053 respectively). Serial 18F-FDG-PET/CT is a potentially reliable non-invasive method to predict recurrence in patients with LARC. Volumetric parameters were the best predictors. This could allow risk-stratification in patients who may benefit from conservative management. This paper will add to the literature in risk-stratifying patients with LARC based on prognosis, using 18F-FDG-PET/CT. This may improve patient outcomes by selecting suitable candidates for conservative management.
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