Investigation of a potential upstream harmonization based on image appearance matching to improve radiomics features robustness: a phantom study.

Autor:	Scapicchio C; Department of Physics, University of Pisa, Pisa, Italy.; National Institute for Nuclear Physics, Pisa Division, Italy., Imbriani M; Department of Physics, University of Pisa, Pisa, Italy., Lizzi F; National Institute for Nuclear Physics, Pisa Division, Italy., Quattrocchi M; Medical Physics Department, Azienda Toscana Nord Ovest Area Nord, Lucca, Italy., Retico A; National Institute for Nuclear Physics, Pisa Division, Italy., Saponaro S; National Institute for Nuclear Physics, Pisa Division, Italy., Tenerani MI; Department of Physics, University of Pisa, Pisa, Italy.; National Institute for Nuclear Physics, Pisa Division, Italy., Tofani A; Medical Physics Department, Azienda Toscana Nord Ovest Area Nord, Lucca, Italy., Zafaranchi A; Department of Physics, University of Pisa, Pisa, Italy.; National Institute for Nuclear Physics, Pisa Division, Italy.; Department of Computer Science, University of Pisa, Pisa, Italy., Fantacci ME; Department of Physics, University of Pisa, Pisa, Italy.; National Institute for Nuclear Physics, Pisa Division, Italy.
Jazyk:	angličtina
Zdroj:	Biomedical physics & engineering express [Biomed Phys Eng Express] 2024 May 07; Vol. 10 (4). Date of Electronic Publication: 2024 May 07.
DOI:	10.1088/2057-1976/ad41e7
Abstrakt:	Objective . Radiomics is a promising valuable analysis tool consisting in extracting quantitative information from medical images. However, the extracted radiomics features are too sensitive to variations in used image acquisition and reconstruction parameters. This limited robustness hinders the generalizable validity of radiomics-assisted models. Our aim is to investigate a possible harmonization strategy based on matching image quality to improve feature robustness. Approach. We acquired CT scans of a phantom with two scanners across different dose levels and percentages of Iterative Reconstruction algorithms. The detectability index was used as a comprehensive task-based image quality metric. A statistical analysis based on the Intraclass Correlation Coefficient was performed to determine if matching image quality/appearance could enhance the robustness of radiomics features extracted from the phantom images. Additionally, an Artificial Neural Network was trained on these features to automatically classify the scanner used for image acquisition. Main results. We found that the ICC of the features across protocols providing a similar detectability index improves with respect to the ICC of the features across protocols providing a different detectability index. This improvement was particularly noticeable in features relevant for distinguishing between scanners. Significance. This preliminary study demonstrates that a harmonization based on image quality/appearance matching could improve radiomics features robustness and heterogeneous protocols can be used to obtain a similar image appearance in terms of the detectability index. Thus protocols with a lower dose level could be selected to reduce the amount of radiation dose delivered to the patient and simultaneously obtain a more robust quantitative analysis. (Creative Commons Attribution license.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu