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Erschienen in:
02.03.2021 | Original Research
The Predictive Value of Baseline Volumetric PET/CT Parameters on Treatment Response and Prognosis in Locally Advanced Rectal Cancer Treated with Neoadjuvant Chemoradiotherapy
Erschienen in: Journal of Gastrointestinal Cancer | Ausgabe 2/2022
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Purpose
To investigate the prognostic effects of baseline volumetric PET/CT parameters including the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and tumor lesion glycolysis (TLG) on treatment response and prognosis in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (NACRT).
Methods
Between 2015 and 2018, 51 patients with LARC treated with NACRT followed by surgery were included in this retrospective study. Patients were divided into 2 groups by tumor regression grade (TRG) as follows: group I = TRG 1 (no detectable cancer cells) + TRG 2 (single cells and/or small groups of cancer cells) and group II = TRG3 (residual tumor outgrown by fibrosis) + TRG 4 (remarkable fibrosis outgrown by tumor cells) + TRG 5 (no fibrosis with extensive residual cancer).
Results
Of the 51 patients, 34 (66.7%) were male. The median age was 55 (range, 37–78) years. According to TRG status, 14 (27.4%) patients were in group I and 37 (72.6%) patients were in group II. The area under the curve (95% CI) was 0.749 (0.593–0.905) in the ROC curve plotted for MTV. The cut-off value for MTV was 12, with 70% sensitivity and 65% specificity. MTV was ≥ 12 in 32 (62.8%) patients. MTV and TLG values were significantly different between groups I and II, whereas there was no significant difference between the groups in terms of SUVmax values (p = 0.006, p = 0.033, and p = 0.673, respectively). The disease-free survival was not reached in patients with MTV < 12 vs. 20 months in those with MTV ≥ 12 (p = 0.323). In multivariate analysis, MTV (OR, 95% Cl, 5.00 [1.17–21.383]) was found to be the factor that affected pathological complete response.
Conclusion
In LARC treated with NACRT, MTV prior to treatment can help predict the response to treatment.