PURPOSE: To investigate the use of FDG-PET/CT before, during and after chemoradiotherapy (CRT) and diffusion-weighted magnetic resonance imaging (DW-MRI) before CRT for the prediction of pathological response (pCR) in rectal cancer patients. MATERIAL AND METHODS: Twenty-two rectal cancer patients treated with long course CRT were included. An FDG-PET/CT was performed prior to the start of CRT, after 10 to 12 fractions of CRT and five weeks after the end of CRT. The tumor was delineated using a gradient based delineation method and the maximal standardized uptake values (SUV(max)) were calculated. A DW-MRI was performed before start of CRT. Mean apparent diffusion coefficients (ADC) were determined. The ΔSUV(max) during and after CRT and the initial ADC values were correlated to the histopathological findings after total mesorectal excision (TME). RESULTS: ΔSUV(max) during and after CRT significantly correlated with the pathological response to treatment (during CRT: ΔSUV(max) = 59% ± 12% for pCR vs. 25% ± 27% if no pCR, p=0.0036; post-CRT: 90% ± 11 for pCR vs. 63% ± 22 if no pCR p=0.013). ROC curve analysis revealed an optimal threshold for ΔSUV(max) of 40% during CRT and 76% after CRT. The initial ADC value was also significantly correlated with pCR (0.94 ± 0.12 × 10(-3) mm(2)/s for pCR vs. 1.2 ± 0.24 × 10(-3) mm(2)/s, p=0.002) and ROC curve analysis revealed an optimal threshold of 1.06 × 10(-3) mm(2)/s. Combining the provided ΔSUV(max) thresholds during and after CRT increased specificity of the prediction (sensitivity 100% and specificity 94%). The combination of the thresholds for the initial ADC value and the ΔSUV(max) during CRT increased specificity of the prediction to a similar level (sensitivity of 100% and specificity of 94%). CONCLUSIONS: The combination of the different time points and the different imaging modalities increased the specificity of the response assessment both during and after CRT.
PURPOSE: To investigate the use of FDG-PET/CT before, during and after chemoradiotherapy (CRT) and diffusion-weighted magnetic resonance imaging (DW-MRI) before CRT for the prediction of pathological response (pCR) in rectal cancerpatients. MATERIAL AND METHODS: Twenty-two rectal cancerpatients treated with long course CRT were included. An FDG-PET/CT was performed prior to the start of CRT, after 10 to 12 fractions of CRT and five weeks after the end of CRT. The tumor was delineated using a gradient based delineation method and the maximal standardized uptake values (SUV(max)) were calculated. A DW-MRI was performed before start of CRT. Mean apparent diffusion coefficients (ADC) were determined. The ΔSUV(max) during and after CRT and the initial ADC values were correlated to the histopathological findings after total mesorectal excision (TME). RESULTS: ΔSUV(max) during and after CRT significantly correlated with the pathological response to treatment (during CRT: ΔSUV(max) = 59% ± 12% for pCR vs. 25% ± 27% if no pCR, p=0.0036; post-CRT: 90% ± 11 for pCR vs. 63% ± 22 if no pCR p=0.013). ROC curve analysis revealed an optimal threshold for ΔSUV(max) of 40% during CRT and 76% after CRT. The initial ADC value was also significantly correlated with pCR (0.94 ± 0.12 × 10(-3) mm(2)/s for pCR vs. 1.2 ± 0.24 × 10(-3) mm(2)/s, p=0.002) and ROC curve analysis revealed an optimal threshold of 1.06 × 10(-3) mm(2)/s. Combining the provided ΔSUV(max) thresholds during and after CRT increased specificity of the prediction (sensitivity 100% and specificity 94%). The combination of the thresholds for the initial ADC value and the ΔSUV(max) during CRT increased specificity of the prediction to a similar level (sensitivity of 100% and specificity of 94%). CONCLUSIONS: The combination of the different time points and the different imaging modalities increased the specificity of the response assessment both during and after CRT.
Authors: Stephanie Nougaret; Hebert Alberto Vargas; Yulia Lakhman; Romain Sudre; Richard K G Do; Frederic Bibeau; David Azria; Eric Assenat; Nicolas Molinari; Marie-Ange Pierredon; Philippe Rouanet; Boris Guiu Journal: Radiology Date: 2016-02-26 Impact factor: 11.105
Authors: Philippe Lambin; Ruud G P M van Stiphout; Maud H W Starmans; Emmanuel Rios-Velazquez; Georgi Nalbantov; Hugo J W L Aerts; Erik Roelofs; Wouter van Elmpt; Paul C Boutros; Pierluigi Granone; Vincenzo Valentini; Adrian C Begg; Dirk De Ruysscher; Andre Dekker Journal: Nat Rev Clin Oncol Date: 2012-11-20 Impact factor: 66.675