Retrospective analysis for the false positive diagnosis of PET-CT scan in lung cancer patients

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Abstract

Early diagnosis is pivotal for prognosis of lung cancer patients. Positron emission tomography/computed tomography (PET-CT) is a useful method for human cancer diagnosis. In this study, we aimed to explore the false positive diagnosis of PET-CT in lung cancer

In total, 754 patients diagnosed with lung cancer via PET-CT were retrospectively collected in this study. Histopathological detection served as gold standard. The diagnostic accuracy of PET-CT was defined as the proportion of lung cancer cases confirmed by pathological diagnosis in the study subjects, and the percentages of misdiagnosed cases represented the false positive diagnosis of PET-CT. Chi-square test and logistic regression analysis were used to analyze the association of pathologically confirmed result with clinical characteristics.

Among all the patients, 705 cases were pathologically confirmed with lung cancer. The diagnostic accuracy of PET-CT was 93.5%, and the false positive rate was 6.50%. Among the false positive patients, inflammatory pseudotumor (42.86%) and tuberculoma (36.74%) were the most pathological types. In the positive detection group, adenocarcinoma (57.16%) and squamous carcinoma (33.19%) were the main pathological types, and 68.09% of the lung cancer patients were at the advanced stages. The false positive rate were related with age, diabetes, interleukin-6 (IL-6) level, and T-spot test (all P < .05).

PET-CT could be a good diagnostic method for lung cancer, but the false positive cases could appear. Detection of inflammatory indicators such as IL-6 and T-spot TB test may help improve the diagnostic accuracy of PET-CT.

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