The role of radiomics in tongue cancer: A new tool for prognosis prediction.
mobile tongue cancer
oral cavity tumor
precision medicine
prognosis prediction
radiomics
Journal
Head & neck
ISSN: 1097-0347
Titre abrégé: Head Neck
Pays: United States
ID NLM: 8902541
Informations de publication
Date de publication:
04 2023
04 2023
Historique:
revised:
08
11
2022
received:
01
07
2022
accepted:
27
12
2022
pubmed:
14
2
2023
medline:
16
3
2023
entrez:
13
2
2023
Statut:
ppublish
Résumé
Radiomics represents an emerging field of precision-medicine. Its application in head and neck is still at the beginning. Retrospective study about magnetic resonance imaging (MRI) based radiomics in oral tongue squamous cell carcinoma (OTSCC) surgically treated (2010-2019; 79 patients). All preoperative MRIs include different sequences (T1, T2, DWI, ADC). Tumor volume was manually segmented and exported to radiomic-software, to perform feature extraction. Statistically significant variables were included in multivariable analysis and related to survival endpoints. Predictive models were elaborated (clinical, radiomic, clinical-radiomic models) and compared using C-index. In almost all clinical-radiomic models radiomic-score maintained statistical significance. In all cases C-index was higher in clinical-radiomic models than in clinical ones. ADC provided the best fit to the models (C-index 0.98, 0.86, 0.84 in loco-regional recurrence, cause-specific mortality, overall survival, respectively). MRI-based radiomics in OTSCC represents a promising noninvasive method of precision medicine, improving prognosis prediction before surgery.
Sections du résumé
BACKGROUND
Radiomics represents an emerging field of precision-medicine. Its application in head and neck is still at the beginning.
METHODS
Retrospective study about magnetic resonance imaging (MRI) based radiomics in oral tongue squamous cell carcinoma (OTSCC) surgically treated (2010-2019; 79 patients). All preoperative MRIs include different sequences (T1, T2, DWI, ADC). Tumor volume was manually segmented and exported to radiomic-software, to perform feature extraction. Statistically significant variables were included in multivariable analysis and related to survival endpoints. Predictive models were elaborated (clinical, radiomic, clinical-radiomic models) and compared using C-index.
RESULTS
In almost all clinical-radiomic models radiomic-score maintained statistical significance. In all cases C-index was higher in clinical-radiomic models than in clinical ones. ADC provided the best fit to the models (C-index 0.98, 0.86, 0.84 in loco-regional recurrence, cause-specific mortality, overall survival, respectively).
CONCLUSION
MRI-based radiomics in OTSCC represents a promising noninvasive method of precision medicine, improving prognosis prediction before surgery.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
849-861Informations de copyright
© 2023 The Authors. Head & Neck published by Wiley Periodicals LLC.
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