Purpose: To predict p53 expression index (p53-EI) based on measurements from computed tomography (CT) for preoperatively assessing pathologies of nodular ground-glass opacities (nGGOs).Methods: Information of 176 cases with nGGOs on high-resolution CT that were pathologically confirmed adenocarcinoma was collected. Diameters, total volumes (TVs), maximum (MAX), average (AVG), and standard deviation (STD) of CT attenuations within nGGOs were measured. p53-EI was evaluated through immunohistochemistry with Image-Pro Plus 6.0. A multiple linear stepwise regression model was established to calculate p53-EI prediction from CT measurements. Receiver-operating characteristic curve analysis was performed to compare the diagnostic performance of variables in differentiating preinvasive adenocarcinoma (PIA), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC).Results: Diameters, TVs, MAX, AVG, and STD showed significant differences among PIAs, MIAs, and IACs (all P-values <0.001), with only MAX being incapable to differentiate MIAs from IACs (P=0.106). The mean p53-EIs of PIAs, MIAs, and IACs were 3.4 +/- 2.0, 7.2 +/- 1.9, and 9.8 +/- 2.7, with significant intergroup differences (all P-values <0.001). An equation was established by multiple linear regression as: p53-EI prediction =0.001TVs + 0.012AVG + 0.022*STD + 9.345, through which p53-EI predictions were calculated to be 4.4%+/- 1.0%, 6.8%+/- 1.3%, and 8.5%+/- 1.4% for PIAs, MIAs, and IACs (Kruskal-Wallis test P<0.001; Tamhane's T2 test: PIA vs MIA P<0.001, MIA vs IAC P<0.001), respectively. Although not significant, p53-EI prediction has a little higher area under the curve (AUC) than the actual one both in differentiating MIAs from PIAs (AUC 0.938 vs 0.914, P=0.263) and in distinguishing IACs from MIAs (AUC 0.812 vs 0.786, P=0.718).Conclusion: p53-EI prediction of nGGOs obtained from CT measurements allows accurately estimating lesions' pathology and invasiveness preoperatively not only from radiology but also from pathology.