- Postdoc. 2020 Vanderbilt University, Chemistry
- Ph.D. 2018 Vanderbilt University, Biomedical Engineering
- M.S. 2016 Vanderbilt University, Biomedical Engineering
- B.S. 2012 Loyola University New Orleans, Physics
- Minor in Math and Chemistry
- 2nd Major in Religious Studies; Christian History
Biomarkers for Noninvasive Lung Cancer Diagnosis
When a computed tomography (CT) scan detects a mass in the lungs (pulmonary nodule) that is suspicious for cancer, physicians have limited options for obtaining a definitive cancer/no cancer diagnosis that does not introduce significant risk to the patient. Invasive procedures, such as bronchoscopies or biopsies, subject patients to general anesthesia and a high risk of a collapsed lung (pneumothorax). Often, the most prudent approach is to take another CT scan after a couple of months and determine if the nodule has grown over time, because growth is a clear sign that the nodule is a likely cancer. However, some nodules grow slowly, or the growth is not easily seen on the follow-up scan. For these reasons, our efforts are focused on improving the accuracy of diagnosis using non-invasive methods.
The compensated interferometer
The compensated interferometer is a new technology developed at Vanderbilt University that can detect molecules in a blood sample at very low levels. Our research group has shown that this technology can be used to measure a molecule (CYFRA 21-1) in blood samples taken from patients with lung nodules, and this measurement can provide a more accurate diagnosis than the standard method of evaluating a CT scan.
To remove some of this uncertainty in analyzing CT scans, our research group has developed a new algorithm for analyzing nodules that uses many 3-dimensional features to evaluate the chance that the nodule is a cancer. These algorithms are more accurate than the standard methods for analyzing a CT scan, and can improve the decision making for how to proceed once a nodule has been detected.
Combination of biomarkers for improved diagnostic accuracy
Each biomarker confers some information about the underlying disease, and combining the radiomic and blood biomarkers with a patient’s medical history allows us to make better predictions than using any of the methods alone. It is the focus of our group to continue refining these methods, incorporating other biomarkers, and ultimately improve patient outcomes.