Purpose: To assess quantitative dual energy computed tomography (DECT) in the diagnosis and characterization of lung cancer.
Material and Methods: A prospective analysis of a cohort of 252 patients (with 256 lung lesions) who underwent diagnostic DECT was performed. Two radiologists contoured lung tumor with a semiautomatic approach. Quantitative DECT parameters were registered as absorbed iodine, effective atomic number, and spectral curves. Statistical analysis was performed to correlate these parameters with malignancy, histology (ADC versus SCC), staging and necrosis status of lung cancer.
Results: Univariate analysis showed that lesion volume was the best predictor to distinguish benign from malignant lesions, with an area under the curve value AUC = 0.73. The asymptote of spectral curves at high energy differentiated both TNMc stages I and II and TNMc stages III and IV as well as ADC from SCC, with an AUC of 0.80. Mean effective atomic number was the best predictor of tumoral necrosis with an AUC of 0.78.
Conclusions: A quantitative DECT approach is statistically significant in lung cancer diagnosis and in the characterization of the stage, ADC versus SCC type, and necrotic status.