The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer
Open accessAbstract
Radiomics provides a comprehensive quantification of tumor phenotypes by extracting and mining large number of quantitative image features. To reduce the redundancy and compare the prognostic characteristics of radiomic features across cancer types, we investigated cancer-specific radiomic feature clusters in four independent Lung and Head & Neck (H&N) cancer cohorts (in total 878 patients). Radiomic features were extracted from the pre-treatment computed tomography (CT) images. Consensus clustering resulted in eleven and thirteen stable radiomic feature clusters for Lung and H&N cancer, respectively. These clusters were validated in independent external validation cohorts using rand statistic (Lung RS = 0.92, p < 0.001, H&N RS = 0.92, p < 0.001). Our analysis indicated both common as well as cancer-specific clustering and clinical associations of radiomic features. Strongest associations with clinical parameters: Prognosis Lung CI = 0.60 ± 0.01, Prognosis H&N CI = 0.68 ± 0.01; Lung histology AUC = 0.56 ± 0.03, Lung stage AUC = 0.61 ± 0.01, H&N HPV AUC = 0.58 ± 0.03, H&N stage AUC = 0.77 ± 0.02. Full utilization of these cancer-specific characteristics of image features may further improve radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor phenotypic characteristics in clinical practice.
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The Potential of Radiomic-Based Phenotyping in Precision Medicine: A Review
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Berenguer, R., Pastor-Juan, M. D. R., Canales-Vázquez, J., Castro-García, M., Villas, M. V., Mansilla Legorburo, F., & Sabater, S. (2018) · Radiology · doi:10.1148/radiol.2018172361 · Cited by 622
Metadata
- Authors
- Parmar, C., Leijenaar, R. T. H., Grossmann, P., Rios Velazquez, E., Bussink, J., Rietveld, D., Rietbergen, M. M., Haibe-Kains, B., Lambin, P., & Aerts, H. J. W. L.
- Venue
- Scientific Reports
- Published
- 2015-06-05
- Volume
- 5
- Issue
- 1
- Pages
- 11044-11044
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2253150690
- Cited by
- 434
- References
- 31
- FWCI
- 35.97
- Type
- journal article
- Language
- en
- Open access
- gold
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- Parmar, C., Leijenaar, R. T. H., Grossmann, P., Rios Velazquez, E., Bussink, J., Rietveld, D., Rietbergen, M. M., Haibe-Kains, B., Lambin, P., & Aerts, H. J. W. L. (2015). Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer. Scientific Reports. https://doi.org/10.1038/srep11044
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