Rule-based Medical Treatment Graph for the Modeling of Hypo- and Hyperglycemia at Onset

Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES2021; 08-10.09.2021, SzczecinThis paper proposes a rule-based medical treatment graph (RB-MTG), a decision support tool that assists physicians in establishing insulin therapy. The RB-MTG models clinical pathways, i.e. the sequences of blood glucose measurements and insulin injections. It provides visualization of alternative clinical pathways, especially those that lead to dangerous states of the patient’s health. By interpreting the RB-MTG, the physician assesses the patient’s condition and plans their insulin therapy. At each phase of the treatment, the RB-MTG suggests the insulin dosage that leads to normoglycemia - the blood glucose level that is the norm for a healthy person. This way, it is possible to avoid the course of the disease that leads to hypo- or hyperglycemia. Physicians have verified the usefulness of our approach

Biomechanical and morphological aspects of abdominal aortic aneurysm growth and rupture

Abdominal aortic aneurysms (AAAs) are dilatations of the abdominal aorta that pose a risk of rupture. The only effective treatment is intervention prior to rupture, but this is also associated with mortality and morbidity. It is therefore important to weigh the risks of intervention with the potential benefit. Current treatment guidelines recommend using the maximal aneurysm diameter (Dmax) as the indicator for rupture risk, and rec- ommend considering intervention in men with AAAs > 55 mm, and >50 mm in women. Patients with small AAAs are put in surveillance, and the Dmax is followed until it reaches the threshold. The current policy is relatively efficient on a population-level but lacks specificity for individuals. Some patients rupture before this threshold, and many remain stable despite passing it. Aneurysm growth is often described as erratic, but measure- ments are affected by several levels of uncertainty. Biomechanical assessment, where 3D models of AAAs from computed tomography angiographies (CTAs) are analysed by finite element analysis, may improve risk prediction. In the first study a population-based cohort of 192 patients with ruptured AAAs and CT imaging available at rupture were studied. A significant portion of patients ruptured with AAAs smaller than 60 mm, 10% of men and 27 % of women. When normalizing Dmax for body surface area (so-called aortic size index) there was, however, was not difference between the sexes. In an analysis of small, ruptured AAAs compared to Dmax, age and sex-matched asymptomatic AAAs, peak wall rupture index (PWRI), but not peak wall stress (PWS) was increased in the ruptured AAAs. In the second study, a cohort of 100 patients with at least three computed tomog- raphy examinations were analysed with 3D morphological and biomechanical analysis. The growth pattern of AAAs appeared continuous and conferred well to a linear growth model. The evolution of the different analysed indices, Dmax, aneurysm volume and bio- mechanical stress did, however, not parallel each other. Intraluminal thrombus (ILT) grew faster than the lumen, but lumen volume growth was more closely related to increase in biomechanical stress. In the third study, a cohort of 67 patients with 109 CTA examinations prior to rupture were identified. The relation between biomechanical variables and time-to-rupture was investigated. In small and medium sized AAAs (< 70 mm), PWRI, but not PWS, was associ- ated with time-to-rupture, also when adjusting for potential confounders, aneurysm size and sex. The results further show that women have an approximately two-fold increased hazard ratio for AAA rupture, compared to men, when adjusted for AAA size. In the fourth study lumen area is indicated as a potentially useful rupture risk marker. Ruptured AAAs, compared to Dmax-matched asymptomatic AAAs, have a larger luminal area, and the luminal area is related to biomechanical stress, even when adjusting for an- eurysm size, or ILT area. In conclusion, the results of this thesis indicate areas of potential improvement in the current care of patients with AAAs, explores the 3D growth of AAAs, and strengthens the potential role for biomechanical analysis. These results may in the future have rele- vance for personalizing timing of treatment for patients with AAAs, and the evaluation of pharmacological therapy for AAAs

Mining clinical pathways for daily insulin therapy of diabetic children

We propose a decision support framework (DSF) assisting insulin therapy of diabetic children. Our DSF relies on a medical treatment graph (MTG), which models and graphically represents clinical pathways. Using the MTG, it is possible to plan and adapt medical decisions dependent upon the current health state of a patient and the progress of the treatment. Our MTG fits well with the requirements of clinical practice. The presented work is a cooperative effort of researchers in computer science and medicine. The MTG model has been thoroughly tested and validated using real-world clinical data. The usefulness of the approach has been confirmed by physicians