The role of radiomics in tongue cancer: A new tool for prognosis prediction

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 pat...

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Bibliographic Details
Published in:Head & neck 2023-04, Vol.45 (4), p.849-861
Main Authors: Mossinelli, Chiara, Tagliabue, Marta, Ruju, Francesca, Cammarata, Giulio, Volpe, Stefania, Raimondi, Sara, Zaffaroni, Mattia, Isaksson, Johannes Lars, Garibaldi, Cristina, Cremonesi, Marta, Corso, Federica, Gaeta, Aurora, Emili, Ilaria, Zorzi, Stefano, Alterio, Daniela, Marvaso, Giulia, Pepa, Matteo, De Fiori, Elvio, Maffini, Fausto, Preda, Lorenzo, Benazzo, Marco, Jereczek‐Fossa, Barbara Alicja, Ansarin, Mohssen
Format: Article
Language:English
Subjects:
Carcinoma, Squamous Cell - diagnostic imaging
Carcinoma, Squamous Cell - therapy
Head & neck cancer
Head and Neck Neoplasms
Humans
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
mobile tongue cancer
Oral cancer
Oral carcinoma
oral cavity tumor
Precision medicine
Prediction models
Prognosis
prognosis prediction
Radiomics
Retrospective Studies
Squamous cell carcinoma
Squamous Cell Carcinoma of Head and Neck
Statistical analysis
Tongue
Tongue Neoplasms - diagnostic imaging
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Summary: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.
ISSN:1043-3074
1097-0347
DOI:10.1002/hed.27299