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Toward Understanding the Robustness of Radiomics Features in CT

D Mackin

D Mackin1*, L Zhang1 , X Fave2 , D Fried2 , J Yang1 , B Taylor3 , E Rodriguez-Rivera4 , C Dodge5 , A Jones1 , L Court1 , (1) UT MD Anderson Cancer Center, Houston, TX, (2) UTH-GSBS, Houston, TX, (3) Baylor College of Medicine, Houston, TX, (4) Houston Methodist Hospital, Houston, TX, (5) Texas Children's Hospital, Houston, TX


SU-D-BRA-5 (Sunday, July 12, 2015) 2:05 PM - 3:00 PM Room: Ballroom A

To gauge the impact of inter-scanner variability on radiomics features in computed tomography (CT).

We compared the radiomics features calculated for 17 scans of the specially designed Credence Cartridge Radiomics (CCR) phantom with those calculated for 20 scans of non–small cell lung cancer (NSCLC) tumors. The scans were acquired at four medical centers using General Electric, Philips, Siemens, and Toshiba CT scanners. Each center used its own routine thoracic imaging protocol. To produce a large dynamic range of radiomics feature values, the CCR phantom has 10 cartridges comprising different materials. The features studied were derived from the neighborhood gray-tone difference matrix or image intensity histogram. To quantify the significance of the inter-scanner variability, we introduced the metric “feature noise”, which compares the ratio of inter-scanner variability and inter-patient variability in decibels, positive values indicating substantial noise. We performed hierarchical clustering based to look for dependence of the features on the scan acquisition parameters.

For 5 of the 10 features studied, the inter-scanner variability was larger than the inter-patient variability. Of the 10 materials in the phantom, shredded rubber seemed to produce feature values most similar to those of the NSCLC tumors. The feature busyness had the greatest feature noise (14.3 dB), whereas texture strength had the least (-14.6 dB). Hierarchical clustering indicated that the features depended in part on the scanner manufacturer, image slice thickness, and pixel size.

The variability in the values of radiomics features calculated for CT images of a radiomics phantom can be substantial relative to the variability in the values of these features calculated for CT images of NSCLC tumors. These inter-scanner differences and their effects should be carefully considered in future radiomics studies.

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