Raimo Sepponen | PubMed Health

PubMed2006

Atrial septal defect: a diagnostic approach.

A simple objective screening method for diagnosis of the atrial septal defect (ASD) is needed. Acoustic signals were collected from 61 children with ASD and 60 with a physiological murmur. The second heart sound (S2) and the spectrum of systolic murmur were analysed. A statistical model was designed using stepwise logistic regression analysis. Significant variables distinguishing pathological form normal findings were the interval between the first heart sound and the beginning of systolic murmur or the respiratory variation of S2, and the frequency of the murmur at its maximum intensity. The area under the ROC curve was 0.922; indicating very good fit of the model and the confidence interval was 0.872-0.971. The sensitivity of the model was 91% and the specificity 73%. The analysis of acoustic findings from the heart is a valuable tool in diagnosing ASD. The next step will be automating this process.

Adolescent↗

PubMed2006

Quantification of mechanical vibration during diffusion tensor imaging at 3 T.

Subjects sense clear mechanical vibrations during diffusion tensor imaging (DTI). These vibrations, likely resulting from diffusion-sensitizing gradients, have been assumed to be of the same strength and phase in all parts of the magnetic resonance imaging (MRI) scanner so that they could be ignored. However, our measurements, carried out from several parts of the MRI scanner and its surroundings using an optical laser-based interferometer, demonstrate an uneven distribution of mechanical vibrations within the scanner. The measurements were performed during DT scanning at 3 T, with various diffusion-weighting parameters, by positioning a phantom in the head coil and/or a human subject on the patient bed. The vibration-related movement was caused by the diffusion-sensitizing gradients and was maximally 0.5 mm with typical settings used in brain imaging. The compensation for eddy currents, done with gradients in our DTI sequence, increased the vibration level by a factor of 1.5 or more with diffusion-weighting parameter b = 1000 s/mm(2) and by a factor of 3 or more with b = 3000 s/mm(2). Mechanical vibrations stayed at an acceptable level with b < or = 1000 s/mm(2), resulting in additional signal losses of 5-17%. Vibration levels might be reduced by adjusting imaging parameters, by modifying the gradient waveforms in the DTI sequence, and by redesigning the mechanics of patient bed to effectively dampen the movements.

Animals↗