Radiomics feature reproducibility under inter-rater variability in segmentations of CT images

Scientific Reports, vol. 10, pp. 12688

Abstract

Identifying image features that are robust with respect to segmentation variability is a tough challenge in radiomics. So far, this problem has mainly been tackled in test-retest analyses. In this work we analyse radiomics feature reproducibility in two phases: first with manual segmentations provided by four expert readers and second with probabilistic automated segmentations using a recently developed neural network (PHiseg). We test feature reproducibility on three publicly available datasets of lung, kidney and liver lesions. We find consistent results both over manual and automated segmentations in all three datasets and show that there are subsets of radiomic features which are robust against segmentation variability and other radiomic features which are prone to poor reproducibility under differing segmentations. By providing a detailed analysis of robustness of the most common radiomics features across several datasets, we envision that more reliable and reproducible radiomic models can be built in the future based on this work.

Authors 6

1. Christoph Haarburger corresponding Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany. christoph.haarburger@lfb.rwth-aachen.de

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany

2. Gustav Anton Müller‐Franzes Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany

3. Leon Weninger Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany

4. Christiane Katharina Kuhl Aachen Department of Diagnostic and Interventional Radiology

   Universitätsklinikum Aachen

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany

5. Daniel Truhn Aachen Department of Diagnostic and Interventional Radiology Institute of Imaging & Computer Vision

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany

6. Dorit Merhof Aachen Institute of Imaging & Computer Vision

   Fraunhofer Institute for Digital Medicine · RWTH Aachen University

   Affiliation as printed

   Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany