Synapse - A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome

A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome Journal Article

Authors:	Vargas, H. A.; Veeraraghavan, H.; Micco, M.; Nougaret, S.; Lakhman, Y.; Meier, A. A.; Sosa, R.; Soslow, R. A.; Levine, D. A.; Weigelt, B.; Aghajanian, C.; Hricak, H.; Deasy, J.; Snyder, A.; Sala, E.
Article Title:	A novel representation of inter-site tumour heterogeneity from pre-treatment computed tomography textures classifies ovarian cancers by clinical outcome
Abstract:	Purpose: To evaluate the associations between clinical outcomes and radiomics-derived inter-site spatial heterogeneity metrics across multiple metastatic lesions on CT in patients with high-grade serous ovarian cancer (HGSOC). Methods: IRB-approved retrospective study of 38 HGSOC patients. All sites of suspected HGSOC involvement on preoperative CT were manually segmented. Gray-level correlation matrix-based textures were computed from each tumour site, and grouped into five clusters using a Gaussian Mixture Model. Pairwise inter-site similarities were computed, generating an inter-site similarity matrix (ISM). Inter-site texture heterogeneity metrics were computed from the ISM and compared to clinical outcomes. Results: Of the 12 inter-site texture heterogeneity metrics evaluated, those capturing the differences in texture similarities across sites were associated with shorter overall survival (inter-site similarity entropy, similarity level cluster shade, and inter-site similarity level cluster prominence; p ≤ 0.05) and incomplete surgical resection (similarity level cluster shade, inter-site similarity level cluster prominence and inter-site cluster variance; p ≤ 0.05). Neither the total number of disease sites per patient nor the overall tumour volume per patient was associated with overall survival. Amplification of 19q12 involving cyclin E1 gene (CCNE1) predominantly occurred in patients with more heterogeneous inter-site textures. Conclusion: Quantitative metrics non-invasively capturing spatial inter-site heterogeneity may predict outcomes in patients with HGSOC. Key Points: • Calculating inter-site texture-based heterogeneity metrics was feasible • Metrics capturing texture similarities across HGSOC sites were associated with overall survival • Heterogeneity metrics were also associated with incomplete surgical resection of HGSOC. © 2017, European Society of Radiology.
Keywords:	survival; ovarian cancer; texture; radiogenomics; radiomics
Journal Title:	European Radiology
Volume:	27
Issue:	9
ISSN:	0938-7994
Publisher:	Springer
Date Published:	2017-09-01
Start Page:	3991
End Page:	4001
Language:	English
DOI:	10.1007/s00330-017-4779-y
PROVIDER:	scopus
PMCID:	PMC5545058
PUBMED:	28289945
DOI/URL:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015108153&doi=10.1007%2fs00330-017-4779-y&partnerID=40&md5=7c025e3e803edbd9d3ab1234d3f74c53
Notes:	Article -- Export Date: 1 September 2017 -- Source: Scopus