To validate a new two dimensional (2-D) bifurcation quantitative coronary angiography (QCA) software.
In the latest edition of the Cardiovascular Angiography Analysis System (CAAS 5.9; Pie Medical ...Imaging, Maastricht, The Netherlands) video-densitometric information is dynamically integrated into the edge-detection algorithm of 11- and 6-segment models to reduce overestimation of small diameters. Furthermore, automatic reference obstruction analysis was optimised. Values of the minimal lumen diameter (MLD), reference vessel diameter (RVD), percent diameter stenosis (DS) and bifurcation angle (BA) for the different bifurcation segment models were validated against precision manufactured plexiglass phantoms. In anteroposterior views, accuracy and precision (mean difference±SD) of 11- and 6-segment models for MLD were 0.013±0.082 mm vs. 0.003±0.100 mm, for RVD -0.030±0.047 mm vs. -0.029±0.045 mm and for DS -0.48±3.66% vs. -0.11±3.97%. In smaller vessel segments (true MLD <0.7 mm), MLD overestimation was reduced. Inter-observer variability for MLD, RVD and DS for either model was ≤0.052 mm, ≤0.043 mm and ≤2.24%, respectively. Agreement between models for MLD, RVD and DS was ±0.076 mm, ±0.021 mm and ±2.53%, respectively. Accuracy and precision for BA were -2.6±3.5°, and variability was ≤1.2°. Accuracy and precision for diameter-derived parameters were slightly decreased in projections with 30° rotation; BA precision dropped to 6.2°.
MLD quantification is improved for true MLD <0.7 mm, resulting in highly accurate and precise diameter measurements over the entire range of phantom diameters. Automatic reference obstruction analysis provides highly accurate, precise and reproducible RVD and DS measurements.
We sought to evaluate the automatic detection of the papillary muscle and to determine its influence on quantitative left ventricular (LV) mass assessment.
Twenty-eight Yorkshire-Landrace swine and ...10 volunteers underwent cardiac magnetic resonance imaging (CMR) of the left ventricle. The variability in measurements of LV papillary muscles traced automatically and manually were compared to intra- and interobserver variabilities. CMR-derived LV mass with the papillary muscle included or excluded from LV mass measurements was compared to true mass at autopsy of the Yorkshire-Landrace swine.
Automatic LV papillary muscle mass from all subjects correlated well with manually derived LV papillary muscle mass measurements (r = 0.84) with no significant bias between both measurements (mean difference +/- SD, 0.0 +/- 1.5 g; P = .98). The variability in results related to the contour detection method used was not statistically significant different compared to intra- and interobserver variabilities (P = .08 and P = .97, respectively). LV mass measurements including the papillary muscle showed significantly less underestimation (-10.6 +/- 7.1 g) with the lowest percentage variability (6%) compared to measurements excluding the papillary muscles (mean underestimation, -15.1 +/- 7.4 g percentage variability, 7%).
The automatic algorithm for detecting the papillary muscle was accurate with variabilities comparable to intra- and interobserver variabilities. LV mass is determined most accurately when the papillary muscles are included in the LV mass measurements. Taken together, these observations warrant the inclusion of automatic contour detection of papillary muscle mass in studies that involve the determination of LV mass.
The aim of this study was to investigate the online assessment feasibility of aortography using videodensitometry in the catheterization laboratory during transcatheter aortic valve replacement ...(TAVR).
Quantitative assessment of regurgitation after TAVR through aortography using videodensitometry is simple, reproducible, and validated in vitro, in vivo, in clinical trials, and in “real-world” patients. However, thus far the assessment has been done offline.
This was a single center, prospective, proof-of-principle, feasibility study. One hundred consecutive patients with aortic stenosis and indications to undergo TAVR were enrolled. All final aortograms were analyzed immediately after acquisition in the catheterization laboratory and were also sent to an independent core laboratory for blinded offline assessment. The primary endpoint of the study was the feasibility of the online assessment of regurgitation (percentage of analyzable cases). The secondary endpoint was the reproducibility of results between the online assessment and the offline analysis by the core laboratory.
Patients’ mean age was 81 ± 7 years, and 56% were men. The implanted valves were either SAPIEN 3 (97%) or SAPIEN 3 Ultra (3%). The primary endpoint of online feasibility of analysis was 92% (95% confidence interval CI: 86% to 97%) which was the same feasibility encountered by the core laboratory (92%; 95% CI: 86% to 97%). Reproducibility assessment showed a high correlation between online and core laboratory evaluations (R2 = 0.87, p < 0.001), with an intraclass correlation coefficient of 0.962 (95% CI: 0.942 to 0.975; p < 0.001).
This study showed high feasibility of online quantitative assessment of regurgitation and high agreement between the online examiner and core laboratory. These results may pave the way for the application of videodensitometry in the catheterization laboratory after TAVR. (Online Videodensitometric Assessment of Aortic Regurgitation in the Cath-Lab OVAL; NCT04047082)
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