Literature DB >> 28647399

Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer.

Ines Joye1, Annelies Debucquoy2, Christophe M Deroose3, Vincent Vandecaveye4, Eric Van Cutsem5, Albert Wolthuis6, André D'Hoore6, Xavier Sagaert7, Mu Zhou8, Olivier Gevaert8, Karin Haustermans9.   

Abstract

BACKGROUND AND
PURPOSE: To explore the integration of imaging and molecular data for response prediction to chemoradiotherapy (CRT) for rectal cancer.
MATERIAL AND METHODS: Eighty-five rectal cancer patients underwent preoperative CRT. 18F-FDG PET/CT and diffusion-weighted imaging (DWI) were acquired before (TP1) and during CRT (TP2) and prior to surgery (TP3). Inflammatory cytokines and gene expression were analysed. Tumour response was defined as ypT0-1N0. Multivariate models were built combining the obtained parameters. Final models were calculated on the data combination with the highest AUC.
RESULTS: Twenty-two patients (26%) achieved ypT0-1N0 response. 18F-FDG PET/CT had worse predictive performance than DWI and T2-volumetry (AUC 0.61±0.04, 0.72±0.03, and 0.72±0.02, respectively). Combining all imaging parameters increased the AUC to 0.81±0.03. Adding cytokines or gene expression did not improve the AUC (AUC of 0.72±0.06 and 0.79±0.04 respectively). Final models combining 18F-FDG PET/CT, DWI, and T2-weighted volumetry at all TPs and using only TP1 and TP3, allowed ypT0-1N0 prediction with a 75% sensitivity, 94% specificity and PPV of 80%.
CONCLUSIONS: Combining 18F-FDG PET/CT, DWI, and T2-weighted MRI volumetry obtained before CRT and prior to surgery may help physicians in selecting rectal cancer patients for organ-preservation.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Chemoradiotherapy; Imaging; Molecular markers; Rectal cancer; Response prediction

Mesh:

Substances:

Year:  2017        PMID: 28647399      PMCID: PMC5641595          DOI: 10.1016/j.radonc.2017.06.013

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  32 in total

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