Model Predictive Control Design to Regulate Thyroid Stimulating Hormone Levels in Patients with Hypothyroidism

Vittal Srinivasan, Purdue University

Abstract

Hypothyroidism is a disease that occurs in the body due to the underacting thyroid gland. The body cannot produce a sufficient hormone level in the thyroid. This leads to an increase in the production of hormones in the pituitary gland. The thyroid is a very significant gland in the body, and the malfunctioning of the thyroid could lead to several other associated conditions like nausea, fatigue, heart conditions, higher cholesterol, and elevated blood pressure. Thus, it is essential to ensure that the levels of thyroid hormones, Triiodothyronine (T3) and Thyroxine (T4), are healthy. The production of these hormones is governed by the hypothalamus-pituitary thyroid (HPT) axis, a part of the endocrine system. When the brain notices that the level of T4 hormone is insufficient in the bloodstream, the hypothalamus gland, located in the brain, produces Thyroid Regulating Hormone (TRH), which signals the pituitary to produce Thyroid Stimulating Hormone (TSH). Once the TSH reaches the thyroid gland, the thyroid is triggered to secrete T3 and T4 into the bloodstream. This creates a negative feedback system. Once sufficient levels of T3 and T4are produced, the hypothalamus and pituitary stop the production of TRH and TSH, respectively. A mathematical model of the HPT axis is presented and simulated for a healthy individual and a patient with hypothyroidism.This disease cannot be cured but can be completely regulated through medication. The standard practice to control hypothyroidism in patients is to prescribe a constant daily dosage of synthetic T4 (i.e., levothyroxine) and, in some cases, an additional dose of synthetic T3(i.e., Liothyronine). Simulation studies are performed where two patients with varying levels of hypothyroidism are prescribed constant doses of synthetic hormones to see the effects of the medication in helping the patients’ hormones reach healthy levels. It is shown that these medications do initially help the patients but are not successful in maintaining healthy ranges of hormones. Thus a controller is designed using model predictive control to prescribe daily doses of medication to the patients. This controller successfully pushes the hormones to healthy ranges in a patient with mild hypothyroidism and controls the hormone levels to significantly healthier ranges in patients with severe hypothyroidism.The inputs are then quantized to be practically implemented in a real patient scenario. Finally, an observer is designed to estimate the state values of the system, as they are not directly accessible to the designer. Thus, this thesis proposes an observer-controller-based compensator that behaves as a ’virtual doctor’ and accurately prescribes daily medication to ensure that the hormone levels of a hypothyroidism patient are entirely controlled.

Degree

M.Sc.

Advisors

Żak, Purdue University.

Subject Area

Design|Clinical psychology|Endocrinology|Neurosciences|Psychology

COinS