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Title: SU-F-R-53: CT-Based Radiomics Analysis of Non-Small Cell Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy

Abstract

Purpose: Stereotactic body radiation therapy (SBRT) is the standard of care for medically inoperable non-small cell lung cancer (NSCLC) patients and has demonstrated excellent local control and survival. However, some patients still develop distant metastases and local recurrence, and therefore, there is a clinical need to identify patients at high-risk of disease recurrence. The aim of the current study is to use a radiomics approach to identify imaging biomarkers, based on tumor phenotype, for clinical outcomes in SBRT patients. Methods: Radiomic features were extracted from free breathing computed tomography (CT) images of 113 Stage I-II NSCLC patients treated with SBRT. Their association to and prognostic performance for distant metastasis (DM), locoregional recurrence (LRR) and survival was assessed and compared with conventional features (tumor volume and diameter) and clinical parameters (e.g. performance status, overall stage). The prognostic performance was evaluated using the concordance index (CI). Multivariate model performance was evaluated using cross validation. All p-values were corrected for multiple testing using the false discovery rate. Results: Radiomic features were associated with DM (one feature), LRR (one feature) and survival (four features). Conventional features were only associated with survival and one clinical parameter was associated with LRR and survival. One radiomic featuremore » was significantly prognostic for DM (CI=0.670, p<0.1 from random), while none of the conventional and clinical parameters were significant for DM. The multivariate radiomic model had a higher median CI (0.671) for DM than the conventional (0.618) and clinical models (0.617). Conclusion: Radiomic features have potential to be imaging biomarkers for clinical outcomes that conventional imaging metrics and clinical parameters cannot predict in SBRT patients, such as distant metastasis. Development of a radiomics biomarker that can identify patients at high-risk of recurrence could facilitate personalization of their treatment regimen for an optimized clinical outcome. R.M. had consulting interest with Amgen (ended in 2015).« less

Authors:
; ; ; ; ; ; ; ;  [1]
  1. Brigham Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA (United States)
Publication Date:
OSTI Identifier:
22626771
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; BIOLOGICAL MARKERS; BIOMEDICAL RADIOGRAPHY; COMPUTERIZED TOMOGRAPHY; HAZARDS; IMAGE PROCESSING; LUNGS; METASTASES; MULTIVARIATE ANALYSIS; NEOPLASMS; PATIENTS; PHENOTYPE; RADIOTHERAPY; VALIDATION

Citation Formats

Huynh, E, Coroller, T, Narayan, V, Agrawal, V, Hou, Y, Romano, J, Franco, I, Mak, R, and Aerts, H. SU-F-R-53: CT-Based Radiomics Analysis of Non-Small Cell Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy. United States: N. p., 2016. Web. doi:10.1118/1.4955824.
Huynh, E, Coroller, T, Narayan, V, Agrawal, V, Hou, Y, Romano, J, Franco, I, Mak, R, & Aerts, H. SU-F-R-53: CT-Based Radiomics Analysis of Non-Small Cell Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy. United States. doi:10.1118/1.4955824.
Huynh, E, Coroller, T, Narayan, V, Agrawal, V, Hou, Y, Romano, J, Franco, I, Mak, R, and Aerts, H. Wed . "SU-F-R-53: CT-Based Radiomics Analysis of Non-Small Cell Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy". United States. doi:10.1118/1.4955824.
@article{osti_22626771,
title = {SU-F-R-53: CT-Based Radiomics Analysis of Non-Small Cell Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy},
author = {Huynh, E and Coroller, T and Narayan, V and Agrawal, V and Hou, Y and Romano, J and Franco, I and Mak, R and Aerts, H},
abstractNote = {Purpose: Stereotactic body radiation therapy (SBRT) is the standard of care for medically inoperable non-small cell lung cancer (NSCLC) patients and has demonstrated excellent local control and survival. However, some patients still develop distant metastases and local recurrence, and therefore, there is a clinical need to identify patients at high-risk of disease recurrence. The aim of the current study is to use a radiomics approach to identify imaging biomarkers, based on tumor phenotype, for clinical outcomes in SBRT patients. Methods: Radiomic features were extracted from free breathing computed tomography (CT) images of 113 Stage I-II NSCLC patients treated with SBRT. Their association to and prognostic performance for distant metastasis (DM), locoregional recurrence (LRR) and survival was assessed and compared with conventional features (tumor volume and diameter) and clinical parameters (e.g. performance status, overall stage). The prognostic performance was evaluated using the concordance index (CI). Multivariate model performance was evaluated using cross validation. All p-values were corrected for multiple testing using the false discovery rate. Results: Radiomic features were associated with DM (one feature), LRR (one feature) and survival (four features). Conventional features were only associated with survival and one clinical parameter was associated with LRR and survival. One radiomic feature was significantly prognostic for DM (CI=0.670, p<0.1 from random), while none of the conventional and clinical parameters were significant for DM. The multivariate radiomic model had a higher median CI (0.671) for DM than the conventional (0.618) and clinical models (0.617). Conclusion: Radiomic features have potential to be imaging biomarkers for clinical outcomes that conventional imaging metrics and clinical parameters cannot predict in SBRT patients, such as distant metastasis. Development of a radiomics biomarker that can identify patients at high-risk of recurrence could facilitate personalization of their treatment regimen for an optimized clinical outcome. R.M. had consulting interest with Amgen (ended in 2015).},
doi = {10.1118/1.4955824},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}