Biomedical subjects

Keijo Ruohonen

Publications and source records attributed to Keijo Ruohonen.

4 recordsLinked to original sources

PubMed2006

Stochastic dynamic model for estimation of rate constants and their variances from noisy and heterogeneous PET measurements.

Tissue heterogeneity, radioactive decay and measurement noise are the main error sources in compartmental modeling used to estimate the physiologic rate constants of various radiopharmaceuticals from a dynamic PET study. We introduce a new approach to this problem by modeling the tissue heterogeneity with random rate constants in compartment models. In addition, the Poisson nature of the radioactive decay is included as a Poisson random variable in the measurement equations. The estimation problem will be carried out using the maximum likelihood estimation. With this approach, we do not only get accurate mean estimates for the rate constants, but also estimates for tissue heterogeneity within the region of interest and other possibly unknown model parameters, e.g. instrument noise variance, as well. We also avoid the problem of the optimal weighting of the data related to the conventionally used weighted least-squares method. The new approach was tested with simulated time-activity curves from the conventional three compartment - three rate constants model with normally distributed rate constants and with a noise mixture of Poisson and normally distributed random variables. Our simulation results showed that this new model gave accurate estimates for the mean of the rate constants, the measurement noise parameter and also for the tissue heterogeneity, i.e. for the variance of the rate constants within the region of interest.

Computer Simulation↗

PubMed2006

Developing Itô stochastic differential equation models for neuronal signal transduction pathways.

Mathematical modeling and simulation of dynamic biochemical systems are receiving considerable attention due to the increasing availability of experimental knowledge of complex intracellular functions. In addition to deterministic approaches, several stochastic approaches have been developed for simulating the time-series behavior of biochemical systems. The problem with stochastic approaches, however, is the larger computational time compared to deterministic approaches. It is therefore necessary to study alternative ways to incorporate stochasticity and to seek approaches that reduce the computational time needed for simulations, yet preserve the characteristic behavior of the system in question. In this work, we develop a computational framework based on the Itô stochastic differential equations for neuronal signal transduction networks. There are several different ways to incorporate stochasticity into deterministic differential equation models and to obtain Itô stochastic differential equations. Two of the developed models are found most suitable for stochastic modeling of neuronal signal transduction. The best models give stable responses which means that the variances of the responses with time are not increasing and negative concentrations are avoided. We also make a comparative analysis of different kinds of stochastic approaches, that is the Itô stochastic differential equations, the chemical Langevin equation, and the Gillespie stochastic simulation algorithm. Different kinds of stochastic approaches can be used to produce similar responses for the neuronal protein kinase C signal transduction pathway. The fine details of the responses vary slightly, depending on the approach and the parameter values. However, when simulating great numbers of chemical species, the Gillespie algorithm is computationally several orders of magnitude slower than the Itô stochastic differential equations and the chemical Langevin equation. Furthermore, the chemical Langevin equation produces negative concentrations. The Itô stochastic differential equations developed in this work are shown to overcome the problem of obtaining negative values.

Computer Simulation↗

PubMed2003

Telemedicine in ophthalmology.

OBJECTIVES: To give an overview of telemedical applications in ophthalmology and to provide background information on new tele-ophthalmological applications. METHODS: We carried out a literature review, a database search and an Internet search. RESULTS: According to published research, the cost-efficiency of telemedicine in ophthalmology has not been established. It has been found to have educational benefits and patients have been satisfied with the possibility of obtaining specialist care without having to travel. CONCLUSIONS: Most studies have been pilot studies and telemedicine is still seldom the primary mode of operation. Technical problems have not been significant, but many open questions about organizational and operational issues remain. Further studies should be directed towards solving these problems and establishing technical standards.

Health Care Costs↗

PubMed2002

Fundus imaging and the telemedical management of diabetes.

Diabetes is the major preventable form of blindness among people of working age in the Western world, despite the improvements in laser photocoagulation treatments. It is known that regular glycaemic control and annual retinal screening of people with diabetes can reduce its incidence. Effective treatment needs to be available but also screening methods which are simple to perform and cost-effective should be implemented. It will be important in future to integrate digital images of the fundus into the health records of diabetic patients. Screening programmes for the detection of diabetic retinopathy aided by image-processing software for processing fundus images will save manpower and increase quality. Before this can happen, we need more clinical studies of store-and-forward techniques, so that they can be standardized and their effectiveness established against that of traditional analogue screening.

Diabetic Retinopathy↗