The role of diffusion-weighted MRI and (18)F-FDG PET/CT in the prediction of pathologic complete response after radiochemotherapy for rectal cancer: a systematic review

After neoadjuvant radiochemotherapy (RCT) for locally advanced rectal cancer, 15-27% of the patients experience a pathological complete response (pCR). This observation raises the question as to whether invasive surgery could be avoided in a selected cohort of patients who obtain a clinical complete response after preoperative RCT. In this respect, there has been growing interest in functional imaging techniques to improve clinical response assessment. This systematic review focuses on the role of diffusion-weighted imaging (DWI) and (18)F-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) in the prediction of pCR after RCT for rectal cancer. A total of 14 publications on DWI and 25 on (18)F-FDG PET/CT were retrieved. Pooled analysis of individual patient data shows both imaging modalities have a low positive predictive value in the prediction of pCR (mean PPV of 54% and 39% for DWI- and (18)F-FDG PET/CT-based parameters respectively). Especially pre-RCT imaging is unable to predict pCR with overall accuracies of 68-72% for DWI and 44% for (18)F-FDG PET/CT. Qualitative DWI assessment 5-10weeks after the end of RCT may outperform apparent diffusion coefficient (ADC)-based DWI-parameters (overall accuracy of 87% vs. 74-78%). Although few data are available, early changes in FDG-uptake seem promising in the prediction of pCR and the role of (18)F-FDG PET/CT during RCT should be further investigated. Quantitative and qualitative (18)F-FDG PET/CT measurements are equally effective in the assessment of pCR after RCT. The major strength of DWI and (18)F-FDG PET/CT lies in the identification of non-responders who are not candidates for organ preservation. Up to now, DWI and (18)F-FDG PET/CT are not accurate enough to safely select patients for organ-sparing strategies. Future research must focus on the integration of functional imaging with clinical data and molecular biomarkers.