Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images.

Background And Purpose: Early Regression Index (ERI) is an image-based parameter based on tumor control probability modelling, that reported interesting results in predicting pathological complete response (pCR) after pre-operative chemoradiotherapy (CRT) in rectal cancer. This study aims to evaluate this parameter for Locally Advanced Cervical Cancer (LACC), considering not only T2-weighted but also diffusion-weighted (DW) Magnetic Resonance (MR) images, comparing it with other image-based parameters such as tumor volumes and apparent coefficient diffusion (ADC).

Materials And Methods: A total of 88 patients affected by LACC (FIGO IB2-IVA) and treated with CRT were enrolled. An MRI protocol consisting in two acquisitions (T2-w and DWI) in two times (before treatment and at mid-therapy) was applied. Gross Tumor Volume (GTV) was delineated and ERI was calculated for both imaging modalities. Surgery was performed for each patient after nCRT: pCR was considered in case of absence of any residual tumor cells. The predictive performance of ERI, GTV volumes (calculated on T2-w and DW MR images) and ADC parameters were evaluated in terms of area (AUC) under the Receiver Operating Characteristic (ROC) curve considering pCR and two-years survival parameters as clinical outcomes.

Results: ERI and GTV volumes calculated on DW MR images (ERI and V) significantly predict pCR (AUC = 0.77 and 0.75 respectively) with results superior to those observed considering T2-w MR images or ADC parameters. Significance was also reported in the prediction of 2-years local control and disease free-survival.

Conclusion: This study identified ERI and V as good predictor of pCR in case of LACC, especially if calculated considering DWI. Using these indicators, it is possible to early identify not responders and modifying the treatment, accordingly.