Pancreatic Regulatory Physiology and Medical Assessment

The pancreas is a vital organ with endocrine and exocrine functions, which play a central role in intermediary metabolism, digestion, and absorption of nutrients. Disorder of the pancreas lead to a variety of diseases, including diabetes mellitus and acute and chronic pancreatitis. Poorly controlled diabetes mellitus can be associated with recurrent acute pancreatitis, which is often diagnosed after excluding other common causes of acute pancreatitis, such as alcohol, cholelithiasis, or metabolic disorders such as hypertriglyceridemia. Patients who develop chronic pancreatitis usually have a history of alcohol abuse and/or nicotine use but is also associated with a 5% risk of developing pancreatic cancer over 20 years. These observations highlight the importance of intact endocrine and exocrine function for long term health and quality of life. This chapter is comprised of three sections. The first section on Pancreatic Regulatory Physiology, deals with (i) Fluid and Electrolyte Transport/Composition of Exocrine Secretion, (ii) Secretion of Major Digestive Enzymes, (iii) Exocrine Pancreas regulation of Digestive Enzyme Secretion, and (iv) Endocrine Pancreas and regulation of glucose metabolism. Section II is on Medical Assessment of Pancreatic Function, involving (i) Direct invasive testing, such as Secretin/CCK/testing, (ii) Direct noninvasive testing, such as Serum Trypsin Assay, (iii) Indirect testing, particularly Serum Glucose Analysis. Section III is on the Oral Glucose Tolerance Test Mathematical Modeling to distinctly detect Diabetic subjects. In Section III, the mathematical simulation of the Oral Glucose Tolerance Test (OGTT) data, of the blood glucose response ``y'' to glucose bolus input ``Gδ(t)'', is represented by means of the governing differential Equation (1.1). This equation has three types of solutions: (i) underdamped response, representing normal subjects, given by Equation (1.2); (ii) overdamped response, representing diabetic subjects, given by Equation (1.3), and (iii) critically damped response, representing at-risk subjects, given by Equation (1.4). In the oral glucose tolerance test (OGTT) analysis, these model solutions are fitted to the monitored blood glucose concentration (BGC) data normalized with respect to the fasting glucose values (see Figure 1.2). By simulating this monitored BGC data by means of the underdamped and overdamped solutions of the OGTT mathematical model, we can determine the model parameters. Figure 1.2 shows distinctly separate simulated curves; the lower curve represents the underdamped solution's simulated curve of the normal subject; the top curve represents the overdamped solution's simulated curve. The differences between the values of these model parameters of subjects, provided in the caption of Figure 1.2 can enable us to distinctly diagnose the subjects. So then in Table 1.6, we are displaying the values of the model parameters for the normal subject and diabetic subjects. We can clearly see the differences in the values of the model parameters for the normal and diabetic subjects. Now we have even gone further and formulated a novel nondimensional diabetic index (NDI), involving the monitored glucose value and the model parameters. This NDI formula is given by Equation (2.8). When this NDI formula is applied to the monitored glucose data, and evaluated by employing the computed values of the model parameters, we obtain NDI = 10.04 for the normal subject, and NDI = 16.2 for the diabetic subject. This NDI number can hence help to diagnose a diabetic subject even better. When we can apply this NDI clinically to a big group of subjects, we can get separate ranges of NDI for normal subjects and diabetic patients, and even an intermediate range for subjects at risk to be diabetic. This can enable appropriate designation of subjects to be normal, diabetic, and at-risk. Then we can even determine the ranges of NDI for normal subjects, diabetic subjects, and at-risk subjects. This is how the mathematical formulation of OGTT can enable us to make accurate diagnosis.