Improving the Diagnostic Specificity of CT for Early Detection of Lung Cancer: 4D CT-Based Pulmonary Nodule Elastometry
Abstract
In this study we propose to develop and validate pulmonary nodule elastometry imaging, a method complementary to CT that has the potential to increase the specificity of screening for early detection of lung cancer. We propose to address the need for greater specificity in lung cancer screening by characterizing a mechanical property of pulmonary lesions, specifically pulmonary nodule (PN) elasticity, in addition to standard anatomic features. We hypothesize that malignant and benign PN can be distinguished more specifically by different elasticities determined from 4D CT images. The specific aims of the study were the development of pulmonary nodule elastometry algorithms based on deformable image processing of 4D CT images and their validation in an animal model and in a retrospective review of over 200 4D CT scans from patients with small malignant pulmonary nodules previously treated with radiation in our department. We have successfully developed the algorithms, and in a first validation we have demonstrated proof of principles that elastometry can distinguish malignant PNs from surrounding lung tissue (a manuscript is submitted and under review/revision). The validation in animal models and the retrospective analysis of the human data is ongoing.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 2014
- Accession Number
- ADA617240
Entities
People
- Billy W Loo
- Peter G Maxim
Organizations
- Stanford University