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Prospective Analysis of18F-FDG PET/CT Predictive Value in Patients with Low Rectal Cancer Treated with Neoadjuvant Chemoradiotherapy and Conservative Surgery
Author(s) -
Artor Niccoli Asabella,
Corinna Altini,
Raffaele De Luca,
Margherita Fanelli,
Domenico Rubini,
Cosimo Caliandro,
Severino Montemurro,
Giuseppe Rubini
Publication year - 2014
Publication title -
biomed research international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 126
eISSN - 2314-6141
pISSN - 2314-6133
DOI - 10.1155/2014/952843
Subject(s) - nuclear medicine , medicine , colorectal cancer , chemoradiotherapy , algorithm , cancer , radiology , radiation therapy , mathematics
This study prospectively assessed 18 F-FDG PET/CT in predicting the response of locally advanced low rectal cancer (LRC) to neoadjuvant chemoradiation (nCRT). Methods . 56 patients treated with chemoradiation underwent two 18 F-FDG PET/CT scans (baseline and 5-6 weeks post-nCRT). 18 F-FDG uptake (SUVmax and SUVmean) and differences between baseline (SUV1) and post-nCRT (SUV2) scans (ΔSUV and RI%) were evaluated. Results were related to the Mandard's TRG and (y)pTNM. Results . 18 F-FDG PET/CT sensitivity, specificity, accuracy, PPV and NPV resulted in 88.6%, 66.7%, 83.92%, 90.7%, and 61.5%. SUV2 resulted in better than SUV1 to predict nCRT response by TRG, with no significant statistical difference between the SUVmax2 and SUVmean2 AUC (0.737 versus 0.736; P = 0.928). The same applies to the (y)pTNM (0.798 versus 0.782; P = 0.192). In relation to the TRG, RI values had a higher AUC than ΔSUV, with no significant difference between RImax and RImean (0.672 versus 0.695; P = 0.292). The same applied to the (y)pTNM (0.742 versus 0.741; P = 0.940). In both cases ΔSUV does not appear to be a good predictive tool. Logistic regression confirmed the better predictive role of SUVmax2 for the (y)pTNM (odds ratio = 1.58) and SUVmean2 for the TRG (odds ratio = 1.87). Conclusions . 18 F-FDG PET/CT can evaluate response to nCRT in LRC, even if more studies are required to define the most significant parameter for predicting pathologic tumor changes.

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