A study on the impact of parameter settings on the biological reproducibility and sensitivity of extracted radiomic features from Full Field Digital Mammography images

Z. Klanecek, T. Wagner, Y. K. Cockmartin, K. Hertl, K. Jarm, M. Krajc,N. W. Marshall, A. Studen, M. Vrhovec, H. Bosmans,R. Jeraj, Y. k Wang

MEDICAL IMAGING 2022: PHYSICS OF MEDICAL IMAGING(2022)

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摘要
Aim: To develop and subsequently perform a systematic study on the impact of parameter settings on the biological reproducibility and sensitivity of extracted radiomic features from Full Field Digital Mammography (FFDM) images for the task of Breast Cancer Risk assessment. Methods: Cranio-caudal (CC) "FOR PRESENTATION" images (88 in total, two centers: Slovenia and Belgium) were used for this study. Biological reproducibility of radiomic features was evaluated with two tests: reproducibility of extracted features between left and right breasts and by reproducibility of extracted features between the original and 4 perturbed images. The quantification was done using the intra-class correlation (ICC) coefficient between values of extracted radiomic features. To determine biological sensitivity, AUC between groups with low and high breast cancer risk was calculated. For the selection of optimal radiomic feature parameters, thresholds of 0.75 and 0.7 were defined for ICC and AUC, respectively. Results: Parameters binCount and distances highly influenced biological reproducibility and sensitivity of specific radiomic features. Parameters weightingNorm and symmetricalGLCM had no effect. Overall, only 12/93 radiomic features passed the reproducibility and sensitivity tests in both centers. For five of these features, parameter ranges were crucial. Reproducibility varied greatly between the centers of Belgium and Slovenia. Conclusions: Rather than single radiomic parameters, parameter ranges were found to be a reasonable description for acceptable biological reproducibility and sensitivity. Overall, 12/93 radiomic features were found to be potential candidates for breast cancer risk prediction tasks, however further analysis is needed before definitive recommendations can be made.
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关键词
radiomics, PyRadiomics, parameter settings, reproducibility, sensitivity, mammography
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