Application of neural networks in the interpretation of impedance cardiovasograms for the diagnoses of peripheral vascular diseases.
An Impedance Cardio-vasograph (ICVG) system has been developed at the Electronics Division, Bhabha Atomic Research Centre (B.A.R.C) for the assessment of Peripheral Blood Flow and has been installed at the Department of Medicine, J.J. Hospital, Mumbai, India. Impedance cardio-vasography (ICVG) gives an indirect assessment of blood volume changes by measurement of normalized rate of change of electrical impedance (N dZ/dt) of the body segment. Parameters like Blood Flow Index (BFI) and Differential Pulse Arrival Time (DPAT) at different locations in both lower extremities (upper thigh, knee, calf and ankle) can be computed from these measurements. This work deals with the analysis of these parameters by a neural network system for obtaining proper diagnosis of subjects with peripheral vascular diseases. The designed network identified the presence of anatomical block or narrowing for most of cases presented to it during testing and also the status of collateral circulation in the lower limbs. The neural network was trained again, with the few cases, which were not predicted correctly. The collaterals after the site of occlusion were classified as good, moderate or poor as an aid to the physician. The network identified cases with athero-sclerotic narrowing satisfactorily and was also able to categorize cases where changes are observed only in one extremity, other remaining normal as in the cases of hemi-Leriche's syndrome. An additional parameter CVS (Coefficient of venous Statis) was calculated which is useful for the diagnosis of primary and secondary varicosity of the veins.
Karamchandani
Sunil
S
Bombay Institute Of Technology Bandra, Mumbai, India. E-mail: skaramchandani@rediffmail.com.
Dixit
M
M
Jain
R
R
Bhowmick
Mita
M