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Data Citation

Lucian Beer, Hilal Sahin,  Ivana Blazic, Hebert Alberto Vargas, Harini Veeraraghavan,  Justin Kirby, Brenda Fevrier-Sullivan, John Freymann, Carl Jaffe, Thomas Conrads, George Maxwell, Kathleen Darcy, Erich Huang, Evis Sala. (2019) Data from Integration of CT-based Qualitative and Radiomic Features with Proteomic Variables in Patients with High-Grade Serous Ovarian Cancer: An Exploratory Analysis. DOI: 10.7937/TCIA.2019.9stoinf1

Description

Objectives

To investigate the association between CT imaging traits and texture metrics with proteomic data in patients with high-grade serous ovarian cancer (HGSOC).

Methods

This retrospective, hypothesis-generating study included 20 patients with HGSOC prior to primary cytoreductive surgery. Two readers independently assessed the contrast-enhanced computed tomography (CT) images and extracted 33 imaging traits, with a third reader adjudicating in the event of a disagreement. In addition, all sites of suspected HGSOC were manually segmented texture features were computed from each tumour site. Three texture features that represented intra-and inter-site tumour heterogeneity were used for analysis. An integrated analysis of transcriptomic and proteomic data identified proteins with conserved expression between primary tumour sites and metastasis. Correlations between protein-abundance and various CT imaging traits and texture features were assessed using the Kendall tau rank correlation-coefficient and the Mann-Whitney U test, whereas the area under the receiver-operating characteristic curve (AUC) was reported as a metric of the strength and the direction of the association. p values < 0.05 were considered significant.

Results

Four proteins were associated with CT-based imaging traits, with the strongest correlation observed between the CRIP2 protein and disease in the mesentery (p<0.001, AUC=0.05). The abundance of three proteins was associated with texture features that represented intra-and inter-site tumour heterogeneity, with the strongest negative correlation between the CKB protein and cluster dissimilarity (p=0.047, 𝜏 =0.326).

Conclusion

This study provides the first insights into the potential associations between standard-of-care CT imaging traits and texture measures of intra-and inter-site heterogeneity, and the abundance of several proteins.

Publication Citation

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  • DICOM Image Data: 20 patient subset of TCGA-OV   
    • Click the Download button above to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever.  
  • Image Analyses, Proteogenomic features, and Clinical data: 
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