Assessment of Pancreatic Physiological and Pathological Characteristics Based on Spectral CT Feature Parameters: A Related Study

Dual-Energy CT (DECT) is a widely recognized technology, especially in its applications for the abdominal and pelvic regions. Pancreatology is an ideal application of the many advantages offered by dual-energy post-processing. DECT can characterize specific tissues or materials/elements, generate virtual unenhanced and monochromatic images, and quantify iodine uptake; these unique capabilities make DECT a perfect technology for supporting tumor detection and characterization as well as treatment monitoring, while also reducing radiation and iodine doses and improving metal artifacts. The pancreas' special endocrine function makes pancreatic tissue highly sensitive to individual variations. Researchers have studied the accumulation of pancreatic fat in patients with obesity and metabolic syndrome, suggesting that obesity, increased age, male gender, hypertension, dyslipidemia, alcohol, and hyperferritinemia can cause ectopic fat accumulation in the pancreas, described analogously to "fatty liver" as "fatty pancreas." Age is also an important factor leading to exocrine dysfunction of the pancreas. Studies on the pancreatic features of patients with type II diabetes have indicated that this condition can severely affect pancreatic atrophy/ irregular morphology and fat deposition. Overall, precise characterization of pancreatic tissue is a crucial part of evaluating diagnoses related to pancreatic diseases. Compared to traditional CT, spectral CT provides ample data that can better assist in diagnosing pancreatic diseases.

However, it corresponds that the pancreas itself is very sensitive to certain non-pancreatic primary diseases, even some special abnormal physiological states (such as obesity). When investigators evaluate the special changes of primary pancreatic diseases, it's challenging to exclude the impacts of these factors completely. For some data abnormalities, it's sometimes unclear whether they are caused solely by primary diseases, or not only by primary diseases, nor is it certain whether the effects of primary diseases and these other states on the data are synergistic or antagonistic. Therefore, collecting and researching pancreatic-related spectral data from patients with non-pancreatic primary diseases coming for consultation is a premise for us to use spectral CT feature parameters to assess the relationship between pancreatic physiological and pathological characteristics.