Core samples for radiomics features that are insensitive to tumor segmentation: method and pilot study using CT images of hepatocellular carcinoma

Sebastian Echegaray; Olivier Gevaert; Rajesh Shah; Aya Kamaya; John Louie; Nishita Kothary; Sandy Napel

doi:10.1117/1.JMI.2.4.041011

18 November 2015 Core samples for radiomics features that are insensitive to tumor segmentation: method and pilot study using CT images of hepatocellular carcinoma

Sebastian Echegaray, Olivier Gevaert, Rajesh Shah, Aya Kamaya, John Louie, Nishita Kothary, Sandy Napel

Author Affiliations +

Journal of Medical Imaging, Vol. 2, Issue 4, 041011 (November 2015). https://doi.org/10.1117/1.JMI.2.4.041011

Abstract

The purpose of this study is to investigate the utility of obtaining “core samples” of regions in CT volume scans for extraction of radiomic features. We asked four readers to outline tumors in three representative slices from each phase of multiphasic liver CT images taken from 29 patients (1128 segmentations) with hepatocellular carcinoma. Core samples were obtained by automatically tracing the maximal circle inscribed in the outlines. Image features describing the intensity, texture, shape, and margin were used to describe the segmented lesion. We calculated the intraclass correlation between the features extracted from the readers’ segmentations and their core samples to characterize robustness to segmentation between readers, and between human-based segmentation and core sampling. We conclude that despite the high interreader variability in manually delineating the tumor (average overlap of 43% across all readers), certain features such as intensity and texture features are robust to segmentation. More importantly, this same subset of features can be obtained from the core samples, providing as much information as detailed segmentation while being simpler and faster to obtain.

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Sebastian Echegaray, Olivier Gevaert, Rajesh Shah, Aya Kamaya, John Louie, Nishita Kothary, and Sandy Napel "Core samples for radiomics features that are insensitive to tumor segmentation: method and pilot study using CT images of hepatocellular carcinoma," Journal of Medical Imaging 2(4), 041011 (18 November 2015). https://doi.org/10.1117/1.JMI.2.4.041011

Published: 18 November 2015

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