Fig 1.
Examples of thrombus assessment by the QCU-CMS image analysis software in OCT image frames of two patients with white (A) and red thrombus (D).
After manual tracing of the thrombi (B,E), attenuation analysis was performed including regions with attenuation values above the designated threshold value (displayed in blue) (C,F). Accurate segmentation of the luminal border of the thrombus and the contrast-filled flow area of the vessel can be seen in C and F. *) OCT catheter, #) guidewire artefact, ¤) thrombus, §) vessel wall. OCT, optical coherence tomography.
Table 1.
Baseline patient characteristics.
Fig 2.
Intra- and interobserver variability of measurement of thrombus attenuation in OCT images using image analysis software.
Scatterplot (left) and Bland-Altman plot (right) of intraobserver (A) and interobserver (B) comparison for median attenuation. OCT, optical coherence tomography; SD, standard deviation.
Table 2.
Interobserver variability of QCU-CMS measurements.
Table 3.
Intraobserver variability of QCU-CMS measurements.
Fig 3.
Relationship of thrombus attenuation score and parameters measured by image analysis software in thrombus areas in OCT images.
Scatterplots for median attenuation (A), 10th percentile of attenuation (B), mean backscatter (C), 10th percentile of backscatter (D), mean grayscale intensity (E) and 10th percentile of grayscale intensity (F). OCT, optical coherence tomography.
Fig 4.
Receiver operating characteristic (ROC) curves of parameters determined by QCU-CMS software in prediction of thrombus type (white vs. red).
Different statistical parameters of attenuation (A), backscatter (B), grayscale intensity (C) and the ratio of 95th percentile of attenuation and median grayscale intensity (D). Perc, percentile.
Table 4.
Results of receiver operating characteristic (ROC) curve analysis of values determined by QCU-CMS software in prediction of thrombus type (white vs. red).