A CT-based radiomics classification model for the prediction of histological type and tumour grade in retroperitoneal sarcoma (RADSARC-R): a retrospective multicohort analysis

Arthur, A., Orton, M.R., Emsley, R. et al. (23 more authors) (2023) A CT-based radiomics classification model for the prediction of histological type and tumour grade in retroperitoneal sarcoma (RADSARC-R): a retrospective multicohort analysis. The Lancet Oncology, 24 (11). pp. 1277-1286. ISSN 1470-2045

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Arthur, A.
  • Orton, M.R.
  • Emsley, R.
  • Vit, S.
  • Kelly-Morland, C.
  • Strauss, D.
  • Lunn, J.
  • Doran, S.
  • Lmalem, H.
  • Nzokirantevye, A.
  • Litiere, S.
  • Bonvalot, S.
  • Haas, R.
  • Gronchi, A.
  • Van Gestel, D.
  • Ducassou, A.
  • Raut, C.P.
  • Meeus, P.
  • Spalek, M.
  • Hatton, M. ORCID logo https://orcid.org/0000-0003-2778-7926
  • Le Pechoux, C.
  • Thway, K.
  • Fisher, C.
  • Jones, R.
  • Huang, P.H.
  • Messiou, C.
Copyright, Publisher and Additional Information:

© 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Keywords: Humans; Male; Female; Aged; Adult; Middle Aged; Aged, 80 and over; Leiomyosarcoma; Retrospective Studies; Sarcoma; Liposarcoma; Soft Tissue Neoplasms; Retroperitoneal Neoplasms; Tomography, X-Ray Computed
Dates:
  • Published: November 2023
  • Published (online): November 2023
  • Accepted: 13 September 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health
Depositing User: Symplectic Sheffield
Date Deposited: 28 Aug 2024 11:47
Last Modified: 28 Aug 2024 11:50
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: 10.1016/s1470-2045(23)00462-x
Related URLs:
Sustainable Development Goals:
  • Sustainable Development Goals: Goal 3: Good Health and Well-Being
Open Archives Initiative ID (OAI ID):

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