Quantitative Assessment of the Parotid Gland Using Computed Tomography Texture Analysis to Detect Patients With Dyslipidemia

Objectives: Proactive diagnosis of dyslipidemia, the most important risk factor for atherosclerosis, is important to reduce the incidence and mortality of cardiovascular disease and stroke. This study aimed to quantitatively assess the parotid gland by using computed tomography (CT) texture analysis to differentiate patients with and without dyslipidemia. Methods: This study included 68 patients (30 men and 38 women; average age, 65.7 years) who had undergone CT for a cerebral checkup (brain dock) at our university hospital. Cases in which the entire parotid gland was not visible in the imaging range, cases in which the contour of the parotid gland was blurred due to extreme metal artifacts, and a case with a parotid tumor were excluded from the study. The texture features of the parotid glands were analyzed using the open-access software LIFEx. The regions of interest were manually placed by tracing the contours of both parotid glands on CT images. The results were tested with the Student's t-test (or Welch's t-test, or Mann–Whitney U test when appropriate). Receiver operating characteristic curve analysis was performed to assess the ability of texture features to predict dyslipidemia. Results: Six histogram features, one gray-level co-occurrent matrix feature, two gray-level run-length matrix features, and two gray-level zone-length matrix features displayed significant differences between the parotid gland of dyslipidemia and non-dyslipidemia patients. Conclusions: CT texture analysis was able to quantitatively assess changes in the parotid gland. CT texture analysis of the parotid gland may have the potential to detect patients with dyslipidemia.