ABSTRACT
In assessing the level of stenosis in extracranial Doppler analysis, spectral analysis has until now been used qualitatively, for the most part. Owing to the many variables affecting the measurements (mainly noise level and instrument setting made subjectively by the operator), the reliability of the inferences on the degree of stenosis is not clearly definable. Under such conditions the need arises for algorithms and systems that can estimate spectral parameters with a higher degree of accuracy, to verify whether reliable inferences can indeed by made or if this technique is only a qualitative one. In the paper a real-time spectral analysis system is described. The system relies on a new spectral estimation algorithm which gives estimates with good robustness with respect to noise. Moreover, a clear measurement procedure which eliminates the many subjective factors affecting the estimates has also been proposed and used. The system has been evaluated with simulated signals and in clinical trials and has shown better performance than the commonly used commercial analysers.
Subject(s)
Arterial Occlusive Diseases/diagnosis , Ultrasonography , Adult , Algorithms , Clinical Trials as Topic , Humans , Models, BiologicalABSTRACT
Doppler instruments are widely used in the diagnosis of vascular diseases: however, the physician generally makes the diagnosis from personal experience, and by subjective evaluation of some quantities related to blood flow (e.g., maximum or mean frequency envelope, or zero-crossing density). In order to obtain more objective criteria, methods based on either spectrum analysis, or on Laplace or other orthogonal transforms have been proposed. An alternative approach to the diagnosis of vascular alterations is proposed, which relies on the modelling of flow signals by means of autoregressive time series. The parameters of the autoregressive model have been used for the detection of alterations. The basis of the method is discussed and some preliminary results are reported.
