Quantitative Doppler in musculoskeletal ultrasonography – suboptimal performance of both experienced and in-training sonographers in selection of the highest Doppler signal image from cine-loops

Abstract

Aims: Doppler ultrasonography assessment is mandatory nowadays for the complete description of rheumatic disease activity. Initially it was performed in semi quantitative way but recently the (fully) quantitative assessment is gaining more interest. In quantitative assessment, the ratio between total colorized and total pixels (CTR) is computed for the whole image or just for the region of interest (ROI). The frame with the highest amount of Doppler signal (also called worst case scenario image – WCSI) is usually the only one analyzed. The technique requires a very precise identification of WCSI from a certain number of consecutive frames, captured from the same position of the US probe, (and in most cases this is done manually). Our study examined the ability of both experienced and in-training sonographers to identify WCSI using a computerized analytical system as the gold standard.Materials and methods: The study analyzed 480 frame selections done in two distinct exercises. The WCSI and other 3 images with a 5%, 10% and respectively 20% lower level of CTR compared with WCSI were packed in one selection. All frames emerging from the same video clip were randomly presented to six experienced and six in training sonographers; the request was to select the frame with the highest CTR (WCSI) from each package (twenty packages in total). A similar exercise was performed with CTRs decreasing in steps of 2%.Results: In the first exercise the WCSI was correctly identified in 79.1% cases and in 67% of cases in the 2nd exercise. The interobserver agreement between experienced and in-trainer evaluators for the 1st exercise was 0.78 and 0.4 in the 2nd exercise.Conclusion: Using computerized analysis as the gold standard, we demonstrated a large heterogeneity across sonographers regarding their ability to identify the best Doppler image even from a small group of frames.

Embedded VR Video Image Control System in the Ideological and Political Teaching System Based on Artificial Intelligence

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