QUANTITATIVE ASSESSMENT OF THE PRESENCE OF A SINGLE LEG SEPARATION INBJORK-SHILEY CONVEXOCONCAVE PROSTHETIC HEART-VALVES

Citation
Ha. Vrooman et al., QUANTITATIVE ASSESSMENT OF THE PRESENCE OF A SINGLE LEG SEPARATION INBJORK-SHILEY CONVEXOCONCAVE PROSTHETIC HEART-VALVES, Investigative radiology, 32(9), 1997, pp. 540-549
Citations number
10
Categorie Soggetti
Radiology,Nuclear Medicine & Medical Imaging
Journal title
ISSN journal
00209996
Volume
32
Issue
9
Year of publication
1997
Pages
540 - 549
Database
ISI
SICI code
0020-9996(1997)32:9<540:QAOTPO>2.0.ZU;2-5
Abstract
RATIONALE AND OBJECTIVES. The authors developed an analytic software p ackage for the objective and reproducible assessment of a single leg s eparation (SLS) in the outlet strut of Bjork-Shiley convexoconcave (BS CC) prosthetic heart valves. METHODS. The radiographic cinefilm record ings of 18 phantom valves (12 intact and 6 SLS) and of 43 patient valv es were acquired. After digitization of regions of interest in a cinef rame, several processing steps were carried out to obtain a one-dimens ional corrected and averaged density profile along the central axis of each strut leg, To characterize the degree of possible separation, tw o quantitative measures were introduced: the normalized pit depth (NPD ) and the depth-sigma ratio (DSR), The group of 43 patient studies was divided into a learning set (25 patients) and a test set (18 patients ). RESULTS. All phantom valves with an SLS were detected (sensitivity, 100%) at a specificity of 100%, The threshold values for the NPD and the DSR to decide whether a fracture was present or not were 3.6 and 2 .5, respectively, On the basis of the visual interpretations of the 25 patient studies (learning set) by an expert panel, it was concluded t hat none of the patients had an SLS, To achieve a 100% specificity by quantitative analysis, the threshold values for the NPD and the DSR we re set at 5.8 and 2.5, respectively, for the patient data. Based on th ese threshold values, the analysis of patient data from the test set r esulted in one false-negative detection and three false-positive detec tions. CONCLUSIONS. An analytic software package for the detection of an SLS was developed, Phantom data showed excellent sensitivity (100%) and specificity (100%), Further research and software development is needed to increase the sensitivity and specificity for patient data.