The predictive value of the change of the number of pixels under different CT value intervals in the CT-occult central lung squamous cell carcinoma and squamous epithelial precancerous lesions

Author:

Zhou Jiaming,Yu Bijun,Guo Peng,Wang Shi

Abstract

Abstract Background Due to the fact that the CT-occult central lung squamous cell carcinoma and squamous epithelial precancerous lesions. (CT-occult CLSCC and SEPL) cannot be detected by lung CT screening, early and timely diagnosis of central lung cancer becomes very difficult, which directly affects the prognosis of patients. Methods We retrospectively review medical records of patients at the Zhejiang Cancer Hospital and enrolled 41 patients with the CT-occult CLSCC and SEPL and 48 patients without the CT-occult CLSCC and SEPL. We compare the clinical characteristics, imaging features and Changes in the number of pixels under different CT value intervals of patients with and without the CT-occult CLSCC and SEPL and we perform univariate and multivariate logistic regression analysis to explore independent factors for the CT-occult CLSCC and SEPL in the patients. Results We demonstrate that pack-years ≥ 20 (OR: 3.848, 95% CI: 1.086 ~ 13.633), the number of pixels change of CT value in interval [-850 ~ -750HU] (OR: 5.302, 95% CI: 1.122 ~ 25.057) and in interval [-900 ~ -850HU] (OR: 3.478, 95% CI: 1.167 ~ 10.365) are independently associated with the CT-occult CLSCC and SEPL in the patients. Ultimately, the logistic model obtained is statistically significant (p < 0.05) and an area under the ROC curve is 0.776 (95% CI: 0.682–0.870). The sensitivity of this model is 90.2% and the specificity is 52.1%. Conclusion The results of this study indicate that in the CT value range [-950 ~ -750HU], when the total number of lung pixels tend to increase towards the region with high CT value, the probability of the occurrence of CT-occult CLSCC and SEPL lesions also increases. Meanwhile, these results have guiding significance for the further study of radiomic.

Publisher

Springer Science and Business Media LLC

Subject

Pulmonary and Respiratory Medicine

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