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J Heart Valve Dis ; 4(6): 649-58; discussion 658-9, 1995 Nov.
Article in English | MEDLINE | ID: mdl-8611981

ABSTRACT

Both closing dynamics and the mechanical condition of a Björk-Shiley Convexo-Concave (BSCC) valve are significant in assessing the risks of outlet strut fracture. Risk of fracture increases with the presence of a pre-existing fracture in one of the two strut legs and with magnitude and frequency of loading. Recent analyses of in vivo data collected in clinical studies, and in vitro data from a computer-controlled pulse duplicator, indicate that the condition of an outlet strut can be evaluated by non-invasive passive acoustic measurement. The technique utilizes heuristic methods to identify features in time and frequency in the closing sound of BSCC valves. Because of patient-to-patient and beat-to-beat variability in the waveforms of closing sounds, the sound of beats are cross-correlated to identify thirteen characteristic waveform groups that are independent of valve strut condition. The groups are used for subsequent acceptance of each closing event. For each group, a Mahalanobis distance technique is used to identify features in time and frequency that characterize the mechanical condition of the BSCC valve. A Volterra expansion is used to optimize the features. A similar approach, where strain gages supply the measured strut load, is used to identify features associated with valve closing load, and to predict outlet strut forces on a beat-for-beat basis in vitro and in sheep. The characterization is based on a set of acoustic recordings made on patients prior to explant of each valve. Analysis is made using blinded and leave-one-out methods, preventing overlap between the data used in training and that used in testing. Results have demonstrated a sensitivity and specificity to strut fracture of 100 percent on a group of 33 patients for whom gold standard data was available. Analysis of additional blinded data will be useful to further quantify the robustness of the detection method. The relative ease with which data can be collected, and the excellent results, indicate that the method may develop into a practical and effective screen for outlet strut condition.


Subject(s)
Acoustics , Heart Valve Prosthesis/instrumentation , Algorithms , Computers , Heart Valve Diseases/physiopathology , Heart Valve Diseases/surgery , Humans , Prosthesis Design , Prosthesis Failure , Sensitivity and Specificity , Vibration
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