Predictive quantitative ultrasound radiomic markers associated with treatment response in head and neck cancer

TRAN, William T., SURAWEERA, Harini, QUAIOIT, Karina, CARDENAS, Daniel, LEONG, Kai X, KARAM, Irene, POON, Ian, JANG, Deok, SANNACHI, Lakshmanan, GANGEH, Mehrdad, TABBARAH, Sami, LAGREE, Andrew, SADEGHI-NAINI, Ali and CZARNOTA, Gregory J (2019). Predictive quantitative ultrasound radiomic markers associated with treatment response in head and neck cancer. Future Science OA, FSOA433.

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Official URL: https://www.future-science.com/doi/10.2144/fsoa-20...
Open Access URL: https://www.future-science.com/doi/pdf/10.2144/fso... (Published)
Link to published version:: https://doi.org/10.2144/fsoa-2019-0048

Abstract

Aim: We aimed to identify quantitative ultrasound (QUS)-radiomic markers to predict radiotherapy response in metastatic lymph nodes of head and neck cancer. Materials &amp; methods: Node-positive head and neck cancer patients underwent pretreatment QUS imaging of their metastatic lymph nodes. Imaging features were extracted using the QUS spectral form, and second-order texture parameters. Machine-learning classifiers were used for predictive modeling, which included a logistic regression, naive Bayes, and k-nearest neighbor classifiers. Results: There was a statistically significant difference in the pretreatment QUS-radiomic parameters between radiological complete responders versus partial responders (p < 0.05). The univariable model that demonstrated the greatest classification accuracy included: spectral intercept (SI)-contrast (area under the curve = 0.741). Multivariable models were also computed and showed that the SI-contrast + SI-homogeneity demonstrated an area under the curve = 0.870. The three-feature model demonstrated that the spectral slope-correlation + SI-contrast + SI-homogeneity-predicted response with accuracy of 87.5%. Conclusion: Multivariable QUS-radiomic features of metastatic lymph nodes can predict treatment response a priori.

Item Type: Article
Additional Information: ** From Future Science Group via Jisc Publications Router ** Licence for this article: http://creativecommons.org/licenses/by/4.0/ **Journal IDs: eissn 2056-5623 **History: published 26-11-2019; online 26-11-2019; published 10-2019; accepted 20-09-2019; submitted 15-04-2019
Uncontrolled Keywords: Research Article, chemoradiation, head and neck carcinoma, predictive assay, quantitative ultrasound, radiation therapy, radiomic
Identification Number: https://doi.org/10.2144/fsoa-2019-0048
Page Range: FSOA433
SWORD Depositor: Justine Gavin
Depositing User: Justine Gavin
Date Deposited: 27 Nov 2019 09:57
Last Modified: 27 Nov 2019 09:57
URI: http://shura.shu.ac.uk/id/eprint/25489

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