Is tumour sphericity an important prognostic factor in patients with lung cancer?
Lung cancer
Prognostic modelling
Radiomics
Tumour shape
Journal
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
ISSN: 1879-0887
Titre abrégé: Radiother Oncol
Pays: Ireland
ID NLM: 8407192
Informations de publication
Date de publication:
02 2020
02 2020
Historique:
received:
15
03
2019
revised:
05
07
2019
accepted:
05
08
2019
pubmed:
2
9
2019
medline:
15
4
2021
entrez:
2
9
2019
Statut:
ppublish
Résumé
Quantitative tumour shape features extracted from radiotherapy planning scans have shown potential as prognostic markers. In this study, we investigated if sphericity of the gross tumour volume (GTV) on planning computed tomography (CT) is an independent predictor of overall survival (OS) in lung cancer patients treated with standard radiotherapy. In the analysis, we considered whether tumour sphericity is correlated with clinical prognostic factors or influenced by the inclusion of lymph nodes in the GTV. Sphericity of single GTV delineation was extracted for 457 lung cancer patients. Relationships between sphericity, and common patient and tumour characteristics were investigated via correlation analysis and multivariate Cox regression to assess prognostic value of GTV sphericity. A subset analysis was performed for 290 nodal stage N0 patients to determine prognostic value of primary tumour sphericity. Sphericity is correlated with clinical variables: tumour volume, mean lung dose, N stage, and T stage. Sphericity is strongly associated with OS (p < 0.001, hazard ratio (HR) (95% confidence interval (CI)) = 0.13 (0.04-0.41)) in univariate analysis. However, this association did not remain significant in multivariate analysis (p = 0.826, HR (95% CI) = 0.83 (0.16-4.31), and inclusion of sphericity to a clinical model did not improve model performance. In addition, no significant relationship between sphericity and OS was detected in univariate (p = 0.072) or multivariate (p = 0.920) analysis of N0 subset. Sphericity correlates clearly with clinical prognostic factors, which are often unaccounted for in radiomic studies. Sphericity is also influenced by the presence of nodal involvement within the GTV contour.
Sections du résumé
BACKGROUND AND PURPOSE
Quantitative tumour shape features extracted from radiotherapy planning scans have shown potential as prognostic markers. In this study, we investigated if sphericity of the gross tumour volume (GTV) on planning computed tomography (CT) is an independent predictor of overall survival (OS) in lung cancer patients treated with standard radiotherapy. In the analysis, we considered whether tumour sphericity is correlated with clinical prognostic factors or influenced by the inclusion of lymph nodes in the GTV.
MATERIALS AND METHODS
Sphericity of single GTV delineation was extracted for 457 lung cancer patients. Relationships between sphericity, and common patient and tumour characteristics were investigated via correlation analysis and multivariate Cox regression to assess prognostic value of GTV sphericity. A subset analysis was performed for 290 nodal stage N0 patients to determine prognostic value of primary tumour sphericity.
RESULTS
Sphericity is correlated with clinical variables: tumour volume, mean lung dose, N stage, and T stage. Sphericity is strongly associated with OS (p < 0.001, hazard ratio (HR) (95% confidence interval (CI)) = 0.13 (0.04-0.41)) in univariate analysis. However, this association did not remain significant in multivariate analysis (p = 0.826, HR (95% CI) = 0.83 (0.16-4.31), and inclusion of sphericity to a clinical model did not improve model performance. In addition, no significant relationship between sphericity and OS was detected in univariate (p = 0.072) or multivariate (p = 0.920) analysis of N0 subset.
CONCLUSION
Sphericity correlates clearly with clinical prognostic factors, which are often unaccounted for in radiomic studies. Sphericity is also influenced by the presence of nodal involvement within the GTV contour.
Identifiants
pubmed: 31472998
pii: S0167-8140(19)33042-7
doi: 10.1016/j.radonc.2019.08.003
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
73-80Subventions
Organisme : Cancer Research UK
ID : C147/A25254
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C147/A18083
Pays : United Kingdom
Informations de copyright
Copyright © 2019 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.