Impact of inter-reader contouring variability on textural radiomics of colorectal liver metastases

Francesco Rizzetto,Angelo Vanzulli,Lorenzo Vassallo,Silvia Ghezzi,Andrea Sartore-Bianchi,Salvatore Siena,Simone Mazzetti,Arianna Defeudis,Daniele Regge,Alberto Torresin,Cristina De Mattia,Silvia Marsoni,Valentina Giannini,Francesca Calderoni

doi:10.1186/s41747-020-00189-8

Abstract

BackgroundRadiomics is expected to improve the management of metastatic colorectal cancer (CRC). We aimed at evaluating the impact of liver lesion contouring as a source of variability on radiomic features (RFs).MethodsAfter Ethics Committee approval, 70 liver metastases in 17 CRC patients were segmented on contrast-enhanced computed tomography scans by two residents and checked by experienced radiologists. RFs from grey level co-occurrence and run length matrices were extracted from three-dimensional (3D) regions of interest (ROIs) and the largest two-dimensional (2D) ROIs. Inter-reader variability was evaluated with Dice coefficient and Hausdorff distance, whilst its impact on RFs was assessed using mean relative change (MRC) and intraclass correlation coefficient (ICC). For the main lesion of each patient, one reader also segmented a circular ROI on the same image used for the 2D ROI.ResultsThe best inter-reader contouring agreement was observed for 2D ROIs according to both Dice coefficient (median 0.85, interquartile range 0.78–0.89) and Hausdorff distance (0.21 mm, 0.14–0.31 mm). Comparing RF values, MRC ranged 0–752% for 2D and 0–1567% for 3D. For 24/32 RFs (75%), MRC was lower for 2D than for 3D. An ICC > 0.90 was observed for more RFs for 2D (53%) than for 3D (34%). Only 2/32 RFs (6%) showed a variability between 2D and circular ROIs higher than inter-reader variability.ConclusionsA 2D contouring approach may help mitigate overall inter-reader variability, albeit stable RFs can be extracted from both 3D and 2D segmentations of CRC liver metastases.

Highlights

Radiomics is expected to improve the management of metastatic colorectal cancer (CRC)
Evidence correlating the textural radiomic features (RFs) extracted from the computed tomography (CT) scans of CRC liver metastases with the clinical outcomes of the patients have accumulated in the last few years
Contouring variability Moving from 3D to 2D region of interest (ROI), an increase in Dice coefficient (DC) and a reduction in Hausdorff distance (HD) was observed

Summary

Introduction

Radiomics is expected to improve the management of metastatic colorectal cancer (CRC). Since 20% of patients with CRC already have liver metastases at the time of diagnosis and up to 50% will develop them within the first 3 years [4], to improve the detection of molecular alterations over time and space of these lesions is crucial to optimise the patient’s management [5]. In this context, great expectations were raised by radiomics, namely the quantitative analysis of medical imaging for the extraction of high-throughput data with diagnostic, prognostic and predictive value [6]. Texture analysis has been used to predict the tumour grade and overall survival of patients with stage IV CRC before treatment [7, 8], the response of liver metastases to firstline chemotherapy [9, 10] and the risk of liver recurrence after hepatic resection of CRC lesions [11]

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