Computer Aided Diagnosis System for Evaluation of Mechanical Artificial Valve

기계식 인공판막 상태 평가를 위한 컴퓨터 보조진단 시스템

  • 이혁수 (안동대학교 정보전자공학교육과)
  • Published : 2004.10.01

Abstract

Clinically, it is almost impossible for a physician to distinguish subtle changes of frequency spectrum by using a stethoscope alone especially in the early stage of thrombus formation. Considering that reliability of mechanical valve is paramount because the failure might end up with patient death, early detection of valve thrombus using noninvasive technique is important. Thus the study was designed to provide a tool for early noninvasive detection of valve thrombus by observing shift of frequency spectrum of acoustic signals with computer aid diagnosis system. A thrombus model was constructed on commercialized mechanical valves using polyurethane or silicon. Polyurethane coating was made on the valve surface, and silicon coating on the sewing ring of the valve. To simulate pannus formation, which is fibrous tissue overgrowth obstructing the valve orifice, the degree of silicone coating on the sewing ring varied from 20%, 40%, 60% of orifice obstruction. In experiment system, acoustic signals from the valve were measured using microphone and amplifier. The microphone was attached to a coupler to remove environmental noise. Acoustic signals were sampled by an AID converter, frequency spectrum was obtained by the algorithm of spectral analysis. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. A return map was applied to evaluate continuous monitoring of valve motion cycle. The in-vivo data also obtained from animals with mechanical valves in circulatory devices as well as patients with mechanical valve replacement for 1 year or longer before. Each spectrum wave showed a primary and secondary peak. The secondary peak showed changes according to the thrombus model. In the mock as well as the animal study, both spectral analysis and 3-layer neural network could differentiate the normal valves from thrombosed valves. In the human study, one of 10 patients showed shift of frequency spectrum, however the presence of valve thrombus was yet to be determined. Conclusively, acoustic signal measurement can be of suggestive as a noninvasive diagnostic tool in early detection of mechanical valve thrombosis.

임상적으로 의사가 청진기를 이용해 초기 혈전이 생긴 기계식 판막 음향신호의 변화를 구분하기는 쉽지 않다. 기계식 판막의 이상은 환자의 죽음을 의미하기 때문에 기계식 판막의 신뢰성과 초기 혈전 현상을 비관혈적으로 조기 진단하는 방법은 매우 중요하다. 이 논문은 컴퓨터 보조진단 시스템과 음향신호의 주파수 스펙트럼의 이동을 관찰하여 기계식 판막의 혈전 현상을 비관혈적으로 평가하는 것을 목적으로 한다. 혈전 모델은 상용화된 기계식 판막에 폴리우레세인과 실리콘을 이용하여 제작하였다. 판막의 표면에는 폴리우레세인을 코팅하고, 봉합링에는 실리콘을 코팅하였다. 봉합링의 주위에서 혈전이 발생하고, 20%, 40%, 60%로 자라나는 현상은 실리콘을 이용하여 제작하였다. 실험 시스템에서 판막의 음향 신호는 마이크로폰과 증폭기를 사용하여 측정하였고, 마이크로폰에는 주위잡음을 제거하기 위해 커플러를 장착하였다. 측정된 음향신호는 A/D 컨버터를 이용하여 샘플링하고, 스펙트럼을 분석하였다. 정상적인 판막과 혈전이 형성된 판막의 주파수 구분을 위해 인공신경망을 구성하였고, 연속적으로 판막의 운동 주기성을 확인하기 위하여 return map을 사용하였다. 생체 내 실험에서는 기계식 판막을 사용하는 순환장치를 장착한 동물과 기계식 판막을 치환 받은 지 1년 이내와 1년이 넘은 환자에게서 데이터를 채집하였다. 실험에서 얻은 데이터 스펙트럼은 두 가지 형태의 첨두치를 보였고, 이중에서 두 번째 첨두치는 혈전의 모델에 따라 변화를 보였다. 생체 내, 외 실험에서 얻은 데이터를 인공신경망에 적용한 결과 정상 판막과 혈전이 생성된 판막을 구분하였고, 환자를 대상으로 한 실험에서는 10명 중 1명이 두 번째 첨두치가 이동하는 결과를 보였지만 다른 방법으로 확인하지는 못했다. 본 논문의 결과는 기계식 판막의 혈전현상을 비침습적으로 조기 진단하고, 상태를 지속적으로 감시할 수 있는 기술적 토대를 제공할 것이다.

Keywords

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