Biomedical subjects

Reijo Takalo

Publications and source records attributed to Reijo Takalo.

4 recordsLinked to original sources

PubMed2006

Tutorial on multivariate autoregressive modelling.

In the present paper, the theoretical background of multivariate autoregressive modelling (MAR) is explained. The motivation for MAR modelling is the need to study the linear relationships between signals. In biomedical engineering, MAR modelling is used especially in the analysis of cardiovascular dynamics and electroencephalographic signals, because it allows determination of physiologically relevant connections between the measured signals. In a MAR model, the value of each variable at each time instance is predicted from the values of the same series and those of all other time series. The number of past values used is called the model order. Because of the inter-signal connections, a MAR model can describe causality, delays, closed-loop effects and simultaneous phenomena. To provide a better insight into the subject matter, MAR modelling is here illustrated with a model between systolic blood pressure, RR interval and instantaneous lung volume.

Biomedical Engineering↗

PubMed2006

Bone oedema predicts erosive progression on wrist MRI in early RA--a 2-yr observational MRI and NC scintigraphy study.

OBJECTIVES: To investigate if disease assessment by contrast-enhanced dynamic and static magnetic resonance imaging (MRI) and quantitative nanocolloid (NC) scintigraphy gives useful additional information in early rheumatoid arthritis (RA). METHODS: Twenty-seven patients with early RA (disease duration < or =12 months) were followed up for 1 yr and 24 of them for 2 yrs with contrast-enhanced MRI and NC scintigraphy of the wrist joint. Synovial inflammation was assessed by measuring time-dependent enhancement rates (E-rate) from dynamic MRI scans and technetium(99m)-labelled nanocolloid ((99m)Tc-NC) uptake from scintigraphy scans. Synovial membrane hypertrophy, bone oedema and erosions were semiquantitatively scored according to the Outcome Measures in Rheumatology Clinical Trials RA-MRI scoring system from static MR images. Response to the treatment was evaluated based on whether or not > or = 50% improvement was achieved in the tender and swollen joint scores and the Health Assessment Questionnaire score, with normal C-reactive protein (CRP) or erythrocyte sedimentation rate (ESR) levels. Progression of the erosion score on wrist MRI was evaluated as the outcome. RESULTS: The baseline MRI bone oedema score (rho= 0.67), MRI synovitis score (rho= 0.57), ESR (rho= 0.56), CRP (rho= 0.48), E-rate (rho= 0.47) and (99m)Tc-NC uptake (rho= 0.45) were related with the change in the MRI erosion score from baseline to 2 yrs (rho= Spearman's correlation). In the multivariate logistic regression model, the bone marrow oedema score was the only baseline variable that predicted erosive progression at 2 yrs' follow-up (OR 4.2, 95% CI 1.3-13.8). The median (interquartile range) change in the erosion score from baseline to 2 yrs was 0 (0, 0) and 4 (2, 5) in the patients with (n= 9) and without (n= 15) a persistent clinical response over the 2 yrs, respectively (P= 0.001). The non-responders who presented with erosive progression from 1 yr to 2 yrs had higher MRI synovitis scores, bone oedema scores, E-rate and (99m)Tc-NC uptake at 1-yr follow-up than the non-responders without progressive bone damage. CONCLUSION: The degree of local synovial inflammation at baseline, evaluated by dynamic and static MRI and quantitative NC scintigraphy, is closely related to the progression of wrist joint erosions during the first 2 yrs of the disease. Furthermore, at follow-up, if no persistent clinical response is achieved, these imaging methods may help to predict future erosiveness and help in clinical therapeutic decision making.

Adult↗

PubMed2006

Tutorial on univariate autoregressive spectral analysis.

In the present paper, the theoretical basis of autoregressive (AR) modelling in spectral analysis is explained in simple terms. Spectral analysis gives information about the frequency content and sources of variation in a time series. The AR method is an alternative to discrete Fourier transform, and the method of choice for high-resolution spectral estimation of a short time series. In biomedical engineering, AR modelling is used especially in the spectral analysis of heart rate variability and electroencephalogram tracings. In AR modelling, each value of a time series is regressed on its past values. The number of past values used is called the model order. An AR model or process may be used in either process synthesis or process analysis, each of which can be regarded as a filter. The AR analysis filter divides the time series into two additive components, the predictable time series and the prediction error sequence. When the prediction error sequence has been separated from the modelled time series, the AR model can be inverted, and the prediction error sequence can be regarded as an input and the measured time series as an output to the AR synthesis filter. When a time series passes through a filter, its amplitudes of frequencies are rescaled. The properties of the AR synthesis filter are used to determine the amplitude and frequency of the different components of a time series. Heart rate variability data are here used to illustrate the method of AR spectral analysis. Some basic definitions of discrete-time signals, necessary for understanding of the content of the paper, are also presented.

Heart Rate↗

PubMed2005

Inhibition of carnitine-acyl transferase I by oxfenicine studied in vivo with [11C]-labeled fatty acids.

METHODS: Anesthetized pigs were studied with [(11)C]-labeled fatty acids (FAs) with carbon chain length ranging from 8 to 16 carbon atoms, during control conditions and during inhibition of carnitine-palmitoyl transferase I (CPT I) with oxfenicine. The myocardial uptake of [(11)C]-FAs from blood was measured together with the relative distribution of [(11)C]-acyl-CoA between rapid mitochondrial oxidation and incorporation into slow turnover lipid pools in the heart. RESULTS: During baseline conditions, the fractional oxidative utilization of palmitate was almost as high as that of carnitine-independent short-chain FAs, unless the carnitine shuttle was inhibited by high levels of lactate. Inhibition of CPT I almost completely blocked the oxidative pathway for palmitic acid and reduced the fractional oxidative utilization, while the rate of oxidative metabolism of acyl-CoA was unaffected. CONCLUSIONS: [(11)C]-Labeled FAs allow rapid oxidation to be well separated from esterification into slow turnover lipid pools in the heart of anaesthetized pigs. The fractional oxidative utilization of [(11)C]-palmitate serves well to characterize, in vivo, the carnitine-dependent transfer of long-chain FAs.

Animals↗