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Delta-radiomics increases multicentre reproducibility: a phantom study

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Abstract

Texture analysis (TA) can provide quantitative features from medical imaging that can be correlated to clinical endpoints. The challenges relevant to robustness of radiomics features have been analyzed by many researchers, as it seems to be influenced by acquisition and reconstruction protocols. Delta-texture analysis (D-TA), conversely, consist in the analysis of TA feature variations at different acquisition times, usually before and after a therapy. Aim of this study was to investigate the influence of different CT scanners and acquisition parameters in the robustness of TA and D-TA. We scanned a commercial phantom (CIRS model 467, Gammex, Middleton, WI, USA), that is used for the calibration of electron density, two times by varying the disposition of plugs, using three different scanners. After the segmentation, we extracted TA features with LifeX and calculated TA features and D-TA features, defined as the variation of each TA parameters extracted from the same position by varying the plugs with the formula (Y–X)/X. The robustness of TA and D-TA features were then tested with intraclass coefficient correlation (ICC) analysis. The reliability of TA parameters across different scans, with different acquisition parameters and ROI positions has shown poor reliability in 12/37 and moderate reliability in the remaining 25/37, with no parameters showing good reliability. The reliability of D-TA, conversely, showed poor reliability in 10/37 parameters, moderate reliability in 10/37 parameters, and good reliability in 17/37 parameters. The comparison between TA and D-TA ICCs showed a significant difference for the whole group of parameters (p:0.004) and for the subclasses of GLCM parameters (p:0.033), whereas for the other subclasses of matrices (GLRLM, NGLDM, GLZLM, Histogram), the difference was not significant. D-TA features seem to be more robust than TA features. These findings reinforce the potentiality for using D-TA features for early assessment of treatment response and for developing tailored therapies. More work is needed in a clinical setting to confirm the results of the present study.

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Acknowledgements

Thanks to the Research Program “Valere” supported by University of Campania “L.Vavitelli”.

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Authors and Affiliations

  1. Unit of Radiation Oncology, Ospedale del Mare, 80147, Naples, Italy

    Valerio Nardone, Cesare Guida & Maria Mormile

  2. Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138, Naples, Italy

    Alfonso Reginelli, Maria Paola Belfiore, Roberta Grassi, Salvatore Cappabianca & Roberto Grassi

  3. Unit of Medical Physics, University Hospital of Siena, 53100, Siena, Italy

    Michelangelo Biondi & Fabrizio Banci Buonamici

  4. Unit of Nuclear Medicine, Ospedale del Mare, 80147, Naples, Italy

    Eugenio Di Giorgio & Marco Spadafora

  5. Unit of Radiation Oncology, University Hospital of Siena, 53100, Siena, Italy

    Paolo Tini & Luigi Pirtoli

  6. Unit of Medical Oncology, Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124, Reggio Calabria, Italy

    Pierpaolo Correale

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  1. Valerio Nardone
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Nardone, V., Reginelli, A., Guida, C. et al. Delta-radiomics increases multicentre reproducibility: a phantom study. Med Oncol 37, 38 (2020). https://doi.org/10.1007/s12032-020-01359-9

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