A radiogenomic dataset of non-small cell lung cancer
| Autor: | Shaimaa Bakr, Hong Zheng, Sylvia K. Plevritis, Ann N. Leung, Sandy Napel, Sebastian Echegaray, Olivier Gevaert, Andrew Quon, Mu Zhou, Joseph B. Shrager, Michael A. Kadoch, Jalen Benson, Kelsey Ayers, Majid Shafiq, Weiruo Zhang, Chuong D. Hoang, Daniel L. Rubin |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Statistics and Probability
medicine.medical_specialty Data Descriptor Lung Neoplasms Gene mutation Library and Information Sciences 030218 nuclear medicine & medical imaging Education 03 medical and health sciences Prognostic markers 0302 clinical medicine Carcinoma Non-Small-Cell Lung Biopsy medicine Carcinoma Cancer genomics Humans Computational models Lung cancer medicine.diagnostic_test business.industry Sequence Analysis RNA Cancer medicine.disease Precision medicine Survival Analysis 3. Good health Computer Science Applications Positron emission tomography 030220 oncology & carcinogenesis Positron-Emission Tomography Cancer imaging Tomography Radiology Statistics Probability and Uncertainty business Tomography X-Ray Computed Information Systems |
| Zdroj: | Scientific Data |
| ISSN: | 2052-4463 |
| DOI: | 10.1038/sdata.2018.202 |
| Popis: | Medical image biomarkers of cancer promise improvements in patient care through advances in precision medicine. Compared to genomic biomarkers, image biomarkers provide the advantages of being non-invasive, and characterizing a heterogeneous tumor in its entirety, as opposed to limited tissue available via biopsy. We developed a unique radiogenomic dataset from a Non-Small Cell Lung Cancer (NSCLC) cohort of 211 subjects. The dataset comprises Computed Tomography (CT), Positron Emission Tomography (PET)/CT images, semantic annotations of the tumors as observed on the medical images using a controlled vocabulary, and segmentation maps of tumors in the CT scans. Imaging data are also paired with results of gene mutation analyses, gene expression microarrays and RNA sequencing data from samples of surgically excised tumor tissue, and clinical data, including survival outcomes. This dataset was created to facilitate the discovery of the underlying relationship between tumor molecular and medical image features, as well as the development and evaluation of prognostic medical image biomarkers. |
| Databáze: | OpenAIRE |
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