Radiomics robustness assessment and classification evaluation: A two-stage method demonstrated on multivendor FFDM

Medical Physics
Kayla RobinsonMaryellen L Giger

Abstract

Radiomic texture analysis is typically performed on images acquired under specific, homogeneous imaging conditions. These controlled conditions may not be representative of the range of imaging conditions implemented clinically. We aim to develop a two-stage method of radiomic texture analysis that incorporates the reproducibility of individual texture features across imaging conditions to guide the development of texture signatures which are robust across mammography unit vendors. Full-field digital mammograms were retrospectively collected for women who underwent screening mammography on both a Hologic Lorad Selenia and GE Senographe 2000D system. Radiomic features were calculated on manually placed regions of interest in each image. In stage one (robustness assessment), we identified a set of nonredundant features that were reproducible across the two different vendors. This was achieved through hierarchical clustering and application of robustness metrics. In stage two (classification evaluation), we performed stepwise feature selection and leave-one-out quadratic discriminant analysis (QDA) to construct radiomic signatures. We refer to this two-state method as robustness assessment, classification evaluation (RACE). These ...Continue Reading

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Citations

Jul 21, 2020·Physics in Medicine and Biology·R Da-AnoM Hatt
Dec 17, 2019·European Journal of Radiology·Guillaume ChassagnonMarie-Pierre Revel
Aug 30, 2021·Medical Physics·Kathryn E KeenanNandita M deSouza
Nov 28, 2021·Medical Physics·Astrid PadillaSaid Pertuz

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