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Radiomics Beyond the Hype: A Critical Evaluation Toward Oncologic Clinical Use.
Horvat, Natally; Papanikolaou, Nikolaos; Koh, Dow-Mu.
Afiliación
  • Horvat N; From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (N.H.); Department of Radiology, University of São Paulo, São Paulo, Brazil (N.H.); Computational Clinical Imaging Group, Champalimaud Foundation, Portugal (N.P.); and Department of Radiology, Royal Marsden Hospital, Downs Rd, Sutton SM2 5PT, United Kingdom (N.P., D.M.K.).
  • Papanikolaou N; From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (N.H.); Department of Radiology, University of São Paulo, São Paulo, Brazil (N.H.); Computational Clinical Imaging Group, Champalimaud Foundation, Portugal (N.P.); and Department of Radiology, Royal Marsden Hospital, Downs Rd, Sutton SM2 5PT, United Kingdom (N.P., D.M.K.).
  • Koh DM; From the Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (N.H.); Department of Radiology, University of São Paulo, São Paulo, Brazil (N.H.); Computational Clinical Imaging Group, Champalimaud Foundation, Portugal (N.P.); and Department of Radiology, Royal Marsden Hospital, Downs Rd, Sutton SM2 5PT, United Kingdom (N.P., D.M.K.).
Radiol Artif Intell ; 6(4): e230437, 2024 Jul.
Article en En | MEDLINE | ID: mdl-38717290
ABSTRACT
Radiomics is a promising and fast-developing field within oncology that involves the mining of quantitative high-dimensional data from medical images. Radiomics has the potential to transform cancer management, whereby radiomics data can be used to aid early tumor characterization, prognosis, risk stratification, treatment planning, treatment response assessment, and surveillance. Nevertheless, certain challenges have delayed the clinical adoption and acceptability of radiomics in routine clinical practice. The objectives of this report are to (a) provide a perspective on the translational potential and potential impact of radiomics in oncology; (b) explore frequent challenges and mistakes in its derivation, encompassing study design, technical requirements, standardization, model reproducibility, transparency, data sharing, privacy concerns, quality control, as well as the complexity of multistep processes resulting in less radiologist-friendly interfaces; (c) discuss strategies to overcome these challenges and mistakes; and (d) propose measures to increase the clinical use and acceptability of radiomics, taking into account the different perspectives of patients, health care workers, and health care systems. Keywords Radiomics, Oncology, Cancer Management, Artificial Intelligence © RSNA, 2024.
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Texto completo: 1 Colección: 01-internacional Asunto principal: Neoplasias Límite: Humans Idioma: En Revista: Radiol Artif Intell Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Asunto principal: Neoplasias Límite: Humans Idioma: En Revista: Radiol Artif Intell Año: 2024 Tipo del documento: Article