Abstract
Lung cancer is the leading cause of cancer death in the United States and worldwide. Most patients are diagnosed at an advanced stage, usually stage III or IV. Identification of lung cancer patients at an early stage might enable oncologists to surgically remove the tumors. Currently, low dose CT scans are used to identify the malignant nodules in high risk patients. However, screening CT scans yield a high rate of falsepositive results. A prediction model was developed for improved discrimination of malignant nodules from benign nodules in patients who underwent lung screening CT. CT images and clinical outcomes of 39 patients were obtained from the National Lung Screening Trial (NLST), National Cancer Institute, National Institute of Health. Images were analyzed to extract computational features relevant to malignancy prediction. A Support Vector Machine (SVM) based model was developed to predict the malignancy of nodules. During pilot studies, our model achieved the following prediction performance: Accuracy of 0.74, sensitivity of 0.85, and specificity of 0.61.
Original language | English |
---|---|
Title of host publication | BIOIMAGING 2016 - 3rd International Conference on Bioimaging, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 |
Editors | James Gilbert, Ana Fred, Carla Quintao, Jan Sliwa, Haim Azhari, Carolina Ruiz, Hugo Gamboa, Hesham Ali |
Pages | 129-133 |
Number of pages | 5 |
ISBN (Electronic) | 9789897581700 |
State | Published - 2016 |
Event | 3rd International Conference on Bioimaging, BIOIMAGING 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 - Rome, Italy Duration: Feb 21 2016 → Feb 23 2016 |
Publication series
Name | BIOIMAGING 2016 - 3rd International Conference on Bioimaging, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 |
---|
Conference
Conference | 3rd International Conference on Bioimaging, BIOIMAGING 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 |
---|---|
Country/Territory | Italy |
City | Rome |
Period | 2/21/16 → 2/23/16 |
Bibliographical note
Publisher Copyright:© 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
Keywords
- Benign nodules
- Malignant nodules
- Prediction model
- Pulmonary nodules
- Support vector machine
ASJC Scopus subject areas
- Biomedical Engineering
- Electrical and Electronic Engineering