Abstract
Objective: The collapse of the internal jugular vein (IJV) regulates intracranial pressure (ICP) in upright body positions. The cross-section area (CSA) is therefore of interest when studying the effects of postural changes in various neurological diseases. We have developed a semi-automatic segmentation method, which tracks the CSA of the IJV in ultrasound movies, and evaluated its performance in three body positions (supine, 16°, 71°). Approach: The proposed method utilized post-processing image filtering combined with a modified snake active contour algorithm. The ultrasound movies were retrospectively analysed (n = 231, 3s, 28 fps) based on previously collected data from 17 healthy volunteers. The computed CSAs (CA) from the segmentation method were compared to manually segmented CSAs (MA) in two frames per movie. Tracking performance were evaluated by visual inspection. Main results: In the supine position, 100% of the ultrasound movies were tracked successfully, and the mean of CA-MA was −4.4 ± 6.9 mm2 (MA, 88.4 ± 50.5 mm2). The most challenging movies occurred in upright body posture where tracking success rate was 90% and mean of CA-MA was −1.4 ± 2.2 mm2 (MA, 12.0 ± 11.1 mm2). The semi-automatic segmentations took 55 s to perform on average (per movie) compared to manual segmentations which took 50 min. Significance: Segmentations made by the proposed method were comparable to manual segmentations in all tilt-angles, however much faster. Efficient and accurate tracking of the CSA of the IJV, with respect to postural changes, could help furthering our understanding of how IJV-biomechanics relates to regulation of intracranial pressure in different neurological diseases and physiological states.
Highlights
Tracking the cross-sectional area (CSA) of the internal jugular vein (IJV) over time in different body postures is relevant for several neurological diseases as the collapse of these veins has been shown to regulate intracranial pressure (ICP) in upright body positions [1]
Since the IJV is accessible with ultrasound, its size and shape have been studied in search for noninvasive assessment methods for different physiological states and indices such as hypovolemia [8] and central venous pressure (CVP) [9, 10]
In this study we have developed a segmentation method that tracks the vessel wall movements of the IJV, and estimates its cross-section area (CSA) from ultrasound movies
Summary
Tracking the cross-sectional area (CSA) of the internal jugular vein (IJV) over time in different body postures is relevant for several neurological diseases as the collapse of these veins has been shown to regulate intracranial pressure (ICP) in upright body positions [1]. Performing frame-by-frame measurements manually is highly time consuming, even for small data sets, suggesting the need for automatic segmentation methods Such an automatic method would have to overcome several obstacles such as: noise interfering with the boundaries of the IJV, large interframe displacements of the vessel walls (due to low frame rate or fast movements of the vessel wall), incomplete boundaries (shadow obscuring the vessel wall), handling very large differences in size and shape (IJVs vary significantly in different body postures and over time) [11,12,13]. The proposed method was evaluated against manual measurements for 231 ultrasound movies in three different body positions (0°, 16° and 71°)
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