Exploring the Role of Quantitative CT in Diagnosing Pancreatic Fat Deposition in Type 2 Diabetes Mellitus.

ABSTRACT

Objective: This study aimed to assess the correlation and consistency between quantitative CT (QCT) and MRI asymmetric echo least squares estimation iterative water-lipid separation sequence (IDEAL-IQ) in determining pancreatic fat content in patients with type 2 diabetes. Methods: A total of 67 patients with type 2 diabetes mellitus who met the inclusion criteria were included in the study. QCT and MRIIDEAL-IQ technologies were utilized to evaluate the patients quantitatively. The pancreatic head, body, and tail regions were examined to measure the fat content and obtain the CT pancreatic fat fraction (CT-PFF) and MRI pancreatic fat fraction (MR-PFF). Pearson correlation analysis examined the relationship between diabetes-related factors and CT-PFF/MR-PFF. Additionally, Bland-Altman analysis assessed the consistency between CT-PFF and MR-PFF. Results: Among the 67 patients, 33 were males and 34 were females. The average age was (66.55±6.23) years, with an average abdominal circumference of (83.34 ± 10.10) cm. The mean values for glycated hemoglobin, fasting blood glucose, BMI, and liver fat content were (6.97±1.07) mmol • L-1, (6.83±1.82) mmol • L-1, (24.02 ± 2.96) kg/m², and (5.28±2.76)%, respectively. Pearson correlation analysis indicated a significant correlation between abdominal circumference, liver fat content, and MR-PFF (r=0.261, 0.267, P < .05). However, no significant correlation was observed between age, glycated hemoglobin, fasting blood glucose, BMI, and MR-PFF (all, P > .05). The minimum and maximum values for CT-PFF among the 67 patients were 7.3% and 60.3%, respectively, with an average value of (19.90±10.61)%. For MR-PFF, the minimum and maximum values were 2% and 48%, respectively, with an average value of (12.21±10.71)%. Pearson correlation analysis demonstrated a significant correlation between CT-PFF and MR-PFF (r = .842, P < .05). Bland-Altman analysis revealed an average bias value of 7.7% and a standard deviation of 5.6% for CT-PFF and MR-PFF. The mean 95% confidence interval ranged from 4.15% to 19.75% (P < .05), with 64 cases falling within this interval and 3 cases falling outside. Conclusion: A correlation exists between pancreatic fat content, abdominal circumference, and liver fat content. Both QCT and MRI can accurately quantify pancreatic fat content, and their correlation and consistency are relatively ideal. QCT technology is particularly suitable for patients with contraindications for magnetic resonance examination.