Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images. (September 2022)

• Record Type: Journal Article
• Authors: Cusumano, Davide; Russo, Luca; Gui, Benedetta; Autorino, Rosa; Boldrini, Luca; D'Erme, Luca; Persiani, Salvatore; Catucci, Francesco; Broggi, Sara; Panza, Giulia; Nardangeli, Alessia; Campitelli, Maura; Ferrandina, Gabriella; Macchia, Gabriella; Fiorino, Claudio; Valentini, Vincenzo; Scambia, Giovanni; Manfredi, Riccardo; Gambacorta, Maria Antonietta
• Is Part Of: Radiotherapy and oncology. Volume 174(2022)
• Page Start: 30
• Page End: 36
• Publication Date: 2022-09
• Subjects: Predictive model -- Image-based biomarker -- Cervical Cancer -- Radiomics; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2022.07.001
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: Early Regression Index (ERI) reported interesting results in response prediction for rectal cancer. The parameter is generally calculated on T2-weighted MR images. We investigated the use of ERI in cervical cancer. We analysed not only T2-w but also diffusion weighted MRI. ERI calculated on DWI shows reliable performance for cervical cancer. Abstract: Background and Purpose: Early Regression Index (ERITCP ) 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 ERITCP 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 ERITCP, 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: ERITCP and GTV volumes calculated on DW MR images (ERIDWI and Vmid_DWI ) 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 ERITCP and Vmid 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.