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CT-based radiomic markers are independent prognosticators of survival in advanced laryngeal cancer: A pilot study.

Lookup NU author(s): Amar Rajgor, Dr Christopher Kui, Dr Josh Cowley, Dr Colin GillespieORCiD, Professor Aileen MillORCiD, Professor Stephen Rushton, Professor Boguslaw ObaraORCiD, Dr Theophile BigirumurameORCiD, Dr Khaled Kallas, Joseph O'Hara, David Hamilton

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2023 Cambridge University Press. All rights reserved.Objective: Advanced laryngeal cancers are clinically complex; there is a paucity of modern decision-making models to guide tumour-specific management. This pilot study aims to identify CT-based radiomic features that may predict survival and enhance prognostication. Methods: Pre-biopsy, contrast-enhanced CT scans were assembled from a retrospective cohort (n=72) with advanced laryngeal cancers (T3-T4). The LifeX software was used for radiomic feature extraction. Two features: shape compacity (irregularity of tumour volume) and GLZLM_GLNU (tumour heterogeneity) were selected via LASSO-Cox regression and explored for prognostic potential. Results: A greater shape compacity (HR 2.89) and GLZLM_GLNU (HR 1.64) were significantly associated with worse 5-year disease-specific survival (p<0.05). Cox regression models yielded a superior C-index when incorporating radiomic features (0.759) versus clinicopathological variables alone (0.655). Conclusions: Two radiomic features were identified as independent prognostic biomarkers. A multi-center prospective study is necessary for further exploration. Integrated radiomic models may refine the treatment of advanced laryngeal cancers.


Publication metadata

Author(s): Rajgor AD, Kui C, McQueen A, Cowley J, Gillespie C, Mill A, Rushton S, Obara B, Bigirumurame T, Kallas K, O'Hara J, Aboagye E, Hamilton DW

Publication type: Article

Publication status: Published

Journal: Journal of Laryngology and Otology

Year: 2023

Volume: 138

Issue: 1

Pages: 685-691

Online publication date: 14/12/2023

Acceptance date: 02/11/2023

Date deposited: 19/02/2024

ISSN (print): 0022-2151

ISSN (electronic): 1748-5460

Publisher: Cambridge University Press

URL: https://doi.org/10.1017/S0022215123002372

DOI: 10.1017/S0022215123002372

ePrints DOI: 10.57711/2vnz-vk71

PubMed id: 38095096


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Funding

Funder referenceFunder name
NIHR

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