CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies.

"Declarations Ethics approval and consent to participateNot applicable. Consent for publicationNot applicable. Competing interestsL.M. Sconfienza is a member of the Insights into Imaging Advisory Editorial Board. He has not taken part in the review or selection process of this article. The remaining authors declare that they have no competing interests related to this article. Competing interests L.M. Sconfienza is a member of the Insights into Imaging Advisory Editorial Board. He has not taken part in the review or selection process of this article. The remaining authors declare that they have no competing interests related to this article."

"Funding Investigator Grant awarded by Fondazione AIRC per la Ricerca sul Cancro for the project “RADIOmics-based machine-learning classification of BOne and Soft Tissue Tumors (RADIO-BOSTT)” (L.M. Sconfienza). The funding source provided financial support without any influence on the study design, on the acquisition and analysis of data, and on the writing of the manuscript."

"The study was registered on the International Prospective Register of Systematic Reviews database with the registration number CRD42023395542. The methods used in the current review paralleled those employed in the previous version [], except for the number of reviewers involved in literature search, study selection, and data extraction, namely three in the current and two in the previous reviews. Additionally, in data extraction, segmentation process and style were grouped under baseline study characteristics in the previous review []. Conversely, these items constituted a separate category in the current version, which also included information regarding radiomic feature types as broad categories."