Application of Quantitative Parameters of Computed Tomography Texture Combined with the Detection of Serum Manganese Superoxide Dismutase in the Diagnosis of Adrenocortical Adenoma.

ABSTRACT

OBJECTIVE: This study aimed to explore the application of quantitative parameters of computed tomography (CT) texture combined with the detection of serum manganese superoxide dismutase (MnSOD) in the diagnosis of adrenocortical adenoma (ACA). METHODS: The study selected 147 patients with suspected ACA received in Yantaishan Hospital from November 2019 to November 2021 as the research objects. These patients were divided into the study group (SG, n = 71, ACA) and the reference group (RG, n = 76, non-ACA) according to the postoperative pathological results to implement CT examination and subsequent serological examination. The quantitative parameters of CT texture and serum MnSOD levels were compared between the two groups, and the receiver operating characteristic curve was used to evaluate the value of single and combined diagnosis of quantitative parameters of CT texture and detection of serum MnSOD. RESULTS: Compared with the RG, the SG had notably lower CT values in the plain scan, venous and delayed phase (p < 0.001) and had overtly higher entropy (p < 0.001). However, no remarkable difference was observed in terms of kurtosis and skewness between the two groups (p > 0.05). The serum MnSOD levels of the SG and RG were 27.26 (24.56, 30.97) U/mL and 43.45 (41.02, 45.08) U/mL, respectively, and the MnSOD level of the SG was significantly lower than that of the RG (p < 0.001). The combined diagnosis of CT entropy parameter and MnSOD detection had higher area under the curve (0.91), sensitivity (88.70%) and specificity (82.90%) than those of each single diagnosis (p < 0.001) and had higher diagnostic efficiency. CONCLUSIONS: The entropy in the quantitative parameters of CT texture and detection of MnSOD can be used for the diagnosis of ACA, and their combined diagnosis effect is good, thus providing a new direction for the clinical identification of the disease.