AR: High-res CT datasets may help quantify lung cancer risk
A new lung cancer risk index (LCRI) could provide a way to determine an individual’s risk for lung cancer, according to a study published in the July issue of Academic Radiology. Researchers analyzed high-resolution CT datasets and pulmonary function testing results to produce a quantitative measure for estimating an individual’s lung cancer risk.

“If the LCRI continues to perform as it did in this preliminary study it could provide a way of identifying an individual’s potential for developing lung cancer,” explained lead investigator Ricardo S.  Avila, senior director of healthcare solutions at Kitware in Saratoga Springs, N.Y. The index seems to perform optimally when lung function is good, potentially providing an early warning of a patient’s lung cancer risk, the authors wrote.

Lung cancer is caused primarily by repeated exposure to carcinogenic particulate matter and noxious gasses with high particulate matter deposition localized to airway bifurcations and the lung periphery. The study shows that quantitative measurement and analysis of these sites has the potential to stratify lung cancer risk. The paper provides the first evidence of a mathematical relationship between loss of lung function, the CT density of upper airway bifurcations and lung cancer.

The study population included 15 patients with early lung cancer and 93 age-matched and pack-year-matched controls with spirometry and CT data. The high-resolution CT subset was comprised of seven patients with cancer and 72 control patients, who were scanned with 1 mm CT slice thickness. Researchers assessed airway bifurcation calcification and lung function via spirometry to produce the LCRI.

Cochran-Mantel-Haenszel analysis and logistic regression tests were used to analyze performance. When researchers applied the Cochran-Mantel-Haenszel test to high resolution patients, they found individuals with higher LCRIs were more likely to have cancer.

In fact, the sensitivity and specificity of the index in the high resolution CT subset were 100 percent and 73 percent, respectively. The cancer detection sensitivity and specificity for all cases was 67 percent and 72 percent , respectively. Independent statistical analysis showed that a 0.03 increase in LCRI was associated with a 1.84 lung cancer odds ratio.

The study identifies a new biomarker for lung cancer and chronic obstructive pulmonary disease. “With further investigation and proper validation studies, there is the potential to provide an objective method for monitoring and managing individual lung cancer risk as well as improving our understanding of lung carcinogenesis,” said Avila. Because CT and spirometry are commonly available the index could be immediately useful if further studies verify early results, he continued.

The index could prove useful in multiple applications. For example, it could help physicians assess the likelihood that a nodule is malignant. “If there isn’t a lot of calcification at bifurcations and lung function is not decreased it may indicate that the lung nodule is benign,” hypothesized Avila.

Physicians might use increases or decreases in a patient’s bifurcation calcifications over time to inform clinical decision making and tailor risk reduction strategies. LCRI might help physicians better identify locations in the lung where lung cancer is more likely to develop, perhaps even on a per lobe basis. Finally, bifurcation sites may one day be used to guide bronchoscopy and obtain tissue samples to better understand the underlying cause of lung tissue damage and help determine a personalized treatment.

LCRI and any potential applications remain in the research realm; however, “we know for sure that we have a new biomarker for lung cancer that provides a new way to risk stratify individuals and could provide insight into disease development,” summarized Avila.