Abstract
Stereotactic ablative radiotherapy (SABR) has recently become a standard treatment option for patients with early-stage lung cancer, which achieves local control rates similar to surgery. Local recurrence following SABR typically presents after one year post-treatment. However, benign radiological changes mimicking local recurrence can appear on CT imaging following SABR, complicating the assessment of response. We hypothesize that subtle changes on early post- SABR CT images are important in predicting the eventual incidence of local recurrence and would be extremely valuable to support timely salvage interventions. The objective of this study was to extract radiomic image features on post-SABR follow-up images for 45 patients (15 with local recurrence and 30 without) to aid in the early prediction of local recurrence. Three blinded thoracic radiation oncologists were also asked to score follow-up images as benign injury or local recurrence. A radiomic signature consisting of five image features demonstrated a classification error of 24%, false positive rate (FPR) of 24%, false negative rate (FNR) of 23%, and area under the receiver operating characteristic curve (AUC) of 0.85 at 2-5 months post-SABR. At the same time point, three physicians assessed the majority of images as benign injury for overall errors of 34-37%, FPRs of 0-4%, and FNRs of 100%. These results suggest that radiomics can detect early changes associated with local recurrence which are not typically considered by physicians. We aim to develop a decision support system which could potentially allow for early salvage therapy of patients with local recurrence following SABR.
Original language | English |
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Title of host publication | Medical Imaging 2016 |
Subtitle of host publication | Computer-Aided Diagnosis |
Publisher | SPIE |
Volume | 9785 |
ISBN (Electronic) | 9781510600201 |
DOIs | |
Publication status | Published - 1 Jan 2016 |
Event | Medical Imaging 2016: Computer-Aided Diagnosis - San Diego, United States Duration: 28 Feb 2016 → 2 Mar 2016 |
Conference
Conference | Medical Imaging 2016: Computer-Aided Diagnosis |
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Country/Territory | United States |
City | San Diego |
Period | 28/02/2016 → 2/03/2016 |
Keywords
- Cancer therapy response assessment
- Classification
- Lung cancer
- Observer studies
- Quantitative imaging biomarkers
- Radiation-induced lung injury
- Radiomics
- Stereotactic radiotherapy