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Radiomics in surgical oncology: applications and challenges

Radiomics in surgical oncology: applications and challenges

Authors :
Travis L. Williams
Lily V. Saadat
Mithat Gonen
Alice Wei
Richard K. G. Do
Amber L. Simpson
Source :
Computer Assisted Surgery, Vol 26, Iss 1, Pp 85-96 (2021)
Publication Year :
2021
Publisher :
Taylor & Francis Group, 2021.

Abstract

Surgery is a curative treatment option for many patients with malignant tumors. Increased attention has focused on the combination of surgery with chemotherapy, as multimodality treatment has been associated with promising results in certain cancer types. Despite these data, there remains clinical equipoise on optimal timing and patient selection for neoadjuvant or adjuvant strategies. Radiomics, an emerging field involving the extraction of advanced features from radiographic images, has the potential to revolutionize oncologic treatment and contribute to the advance of personalized therapy by helping predict tumor behavior and response to therapy. This review analyzes and summarizes studies that use radiomics with machine learning in patients who have received neoadjuvant and/or adjuvant chemotherapy to predict prognosis, recurrence, survival, and therapeutic response for various cancer types. While studies in both neoadjuvant and adjuvant settings demonstrate above average performance on ability to predict progression-free and overall survival, there remain many challenges and limitations to widespread implementation of this technology. The lack of standardization of common practices to analyze radiomics, limited data sharing, and absence of auto-segmentation have hindered the inclusion and rapid adoption of radiomics in prospective, clinical studies.

Details

Language :
English
ISSN :
24699322
Volume :
26
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Computer Assisted Surgery
Publication Type :
Academic Journal
Accession number :
edsdoj.f55a5227e64e42489be57a0a61fdeaab
Document Type :
article
Full Text :
https://doi.org/10.1080/24699322.2021.1994014