Journal
RADIOTHERAPY AND ONCOLOGY
Volume 120, Issue 2, Pages 258-266Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.radonc.2016.05.024
Keywords
Radiomics; Imaging; Stereotactic body radiation therapy; Lung cancer
Funding
- National Institute of Health [NIH-USA U24CA194354, NIH-USA U01CA190234]
- Kaye Scholar Award
- Brigham and Women's Hospital Department of Radiation Oncology Clinical Translational Grant
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Background: Radiomics uses a large number of quantitative imaging features that describe the tumor phenotype to develop imaging biomarkers for clinical outcomes. Radiomic analysis of pre-treatment computed-tomography (CT) scans was investigated to identify imaging predictors of clinical outcomes in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiation therapy (SBRT). Materials and methods: CT images of 113 stage I-II NSCLC patients treated with SBRT were analyzed. Twelve radiomic features were selected based on stability and variance. The association of features with clinical outcomes and their prognostic value (using the concordance index (CI)) was evaluated. Radiomic features were compared with conventional imaging metrics (tumor volume and diameter) and clinical parameters. Results: Overall survival was associated with two conventional features (volume and diameter) and two radiomic features (LoG 3D run low gray level short run emphasis and stats median). One radiomic feature (Wavelet LLH stats range) was significantly prognostic for distant metastasis (CI = 0.67, q-value < 0.1), while none of the conventional and clinical parameters were. Three conventional and four radiomic features were prognostic for overall survival. Conclusion: This exploratory analysis demonstrates that radiomic features have potential to be prognostic for some outcomes that conventional imaging metrics cannot predict in SBRT patients. (C) 2016 Elsevier Ireland Ltd. All rights reserved.
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