Early identifying arteriosclerosis in newly diagnosed type 2 diabetes (T2D) patients could contribute to choosing proper subjects for early prevention. Here, we aimed to investigate whether radiomic intermuscular adipose tissue (IMAT) analysis could be used as a novel marker to indicate arteriosclerosis in newly diagnosed T2D patients.
A total of 549 patients with newly diagnosed T2D were included in this study. The clinical information of the patients was recorded and the carotid plaque burden was used to indicate arteriosclerosis. Three models were constructed to evaluate the risk of arteriosclerosis: a clinical model, a radiomics model (a model based on IMAT analysis proceeded on chest CT images), and a clinical-radiomics combined model (a model that integrated clinical-radiological features). The performance of the three models were compared using the area under the curve (AUC) and DeLong test. Nomograms were constructed to indicate arteriosclerosis presence and severity. Calibration curves and decision curves were plotted to evaluate the clinical benefit of using the optimal model.
The AUC for indicating arteriosclerosis of the clinical-radiomics combined model was higher than that of the clinical model [0.934 (0.909, 0.959) vs. 0.687 (0.634, 0.730),
Radiomics IMAT analysis could be a novel marker for indicating arteriosclerosis in patients with newly diagnosed T2D. The constructed nomograms provide a quantitative and intuitive way to assess the risk of arteriosclerosis, which may help clinicians comprehensively analyse radiomics characteristics and clinical risk factors more confidently.