Data Citation
Grove, Olya, Berglund, Anders E., Schabath, Matthew B., Aerts, Hugo J.W.L., Dekker, Andre, Wang, Hua, … Gillies, Robert J. (2015). Data from: Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2015.A6V7JIWX
Description
In this work, two CT features were developed to quantitatively describe lung adenocarcinomas by scoring tumor shape complexity and intratumor density variation using routinely obtained diagnostic CT scans. The features systematically scored tumors and identified imaging phenotypes which exhibited survival differences. The features were extracted from routinely obtained CT images and were reproducible and stable despite the inherent clinical image acquisition variability. Our results suggest that quantitative imaging features can be used as an additional diagnostic tool in management of lung adenocarcinomas.
Publication Citation
Quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma. Grove O, Berglund AE, Schabath MB, Aerts HJ, Dekker A, Wang H, Velazquez ER, Lambin P, Gu Y, Balagurunathan Y, Eikman E, Gatenby RA, Eschrich S, Gillies RJ. PLoS One. 2015 Mar 4;10(3):e0118261. doi: 10.1371/journal.pone.0118261. eCollection 2015.
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- Image Data: DICOM
- Clinical Data: Survival data (status: dead or alive, survival time in months) and pathological stage (TNM)