Application value of double-layer spectral detector CT in differentiating central lung cancer from atelectasis

Central lung cancer with obstructive atelectasis is very common in clinical practice. Determination of the tumor borderline is important. Conventional computed tomography (CT) alone may not be sufficiently accurate to distinguish central lung cancer from obstructive atelectasis. Spectral CT can improve the soft-tissue resolution greatly. In this study, we evaluated the application value of double-layer spectral detector CT in differentiating central lung cancer from atelectasis.

A total of 51 patients (37 males) with pathologically confirmed central lung cancer accompanied by atelectasis were enrolled. The rates of differentiation between tumors and atelectasis were retrospectively analyzed using conventional CT and three types of spectral images (40 keV virtual monoenergetic imaging, iodine density map, and their fusion image) of unenhanced scans as well as arterial and venous phases. Cochran's Q test and Friedman test were used to compare the differentiation rates and the maximal diameters of the tumors in each image.

Among the 51 cases, conventional CT, 40 keV monoenergetic, iodine density, and their fusion images of the venous phase were successful in differentiating tumors from atelectasis in 17 (33.33%), 35 (68.63%), 39 (76.47%), and 38 (74.51%) cases, respectively. The differentiation rates of the 40 keV monoenergetic, iodine density, and fusion images were significantly higher than those of conventional images (χ2=-0.35, -0.43, and -0.41, respectively, all P<0.001). There were no significant differences in the differentiation rates among the 40 keV monoenergetic, iodine density, and fusion images (χ2=-0.06, -0.08, 0.02, respectively, all P=1.00). The maximal tumor diameters in the four images did not significantly differ (χ2=3.61, P=0.31). Conventional and spectral images of unenhanced and arterial phases could not/barely identify the tumor borderlines.

Venous-phase spectral images of double-layer spectral detector CT can differentiate most central lung cancers from atelectasis, and the maximal diameter measurement of the tumor is reliable. Double-layer spectral detector CT can accurately identify the borderlines of most central lung cancers through spectral images during routine CT examinations without requiring other imaging modalities. Therefore, this method has considerable clinical value for applications in tumor staging, efficacy evaluation, and radiotherapy.