Quantitative analysis of energy spectrum CT in differential diagnosis of peripheral lung cancer and tuberculosis in unenhanced phase / 中国医学影像技术

ABSTRACT

Objective To investigate the value of quantitative analysis of spectrum CT in the differential diagnosis of lung cancer and tuberculosis in unenhanced phase.Methods Data of 51 patients with solitary pulmonary nodules or masses confirmed by pathology who underwent chest unenhanced spectrum CT were retrospectively analyzed.There were 36 cases of peripheral lung cancer (lung cancer group) and 15 cases of tuberculosis (tuberculosis group).The differences of 40～ 140 keV single energy CT value,shape and slope of energy spectrum attenuation curve,different base material of concentration values and effective atomic number (Eff-Z) between the two groups were compared.Results The single energy CT values of 40～70 keV in lung cancer group were higher than those in tuberculosis group (all P＜0.05),while no significant difference of the single energy CT values of 80～140 keV were found in both two groups (all P＞0.05).The shape of energy spectrum attenuation curve of lung cancer group was fast express reduction (36/36,100％).The energy spectrum attenuation curve of tuberculosis group showed walked straightly (11/15,73.33％) and back up type (4/15,26.67％).The slope of the energy spectrum attenuation curve in lung cancer group (K40～ 65 key,K65～90 kev,K90～140 kev)were higher than those in tuberculosis group (all P＜0.01).The calcium (water) concentration of lung cancer group was higher than that of tuberculosis group (P＜0.01),while the lipid (water) concentration of lung cancer group was lower than that of tuberculosis group (P＜0.01).The water (calcium) concentration in both groups was not statistically different (P=0.10).The Eff-Z of lung cancer group was higher than that of the tuberculosis group (P＜0.01).Conclusion The peripheral lung cancer and the tuberculosis have different energy spectrum CT quantitative parameters in unenhanced phase,which can provide valuable informations for diagnosis.