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Assessment of respirophasic fluctuations in the diameter of the inferior vena cava (IVC) is detrimentally affected by its concomitant displacements. This study was aimed at presenting and validating a method to compensate for IVC movement artifacts while continuously measuring IVC diameter in an automated fashion (with minimal interaction with the user) from a longitudinal B-mode ultrasound clip. Performance was tested on both experimental ultrasound clips collected from four healthy patients and simulations, implementing rigid IVC displacements and pulsation. Compared with traditional M-mode measurements, the new approach systematically reduced errors in caval index assessment (range over maximum diameter value) to an extent depending on individual vessel geometry, IVC movement and choice of the M-line (the line along which the diameter is computed). In experimental recordings, this approach identified both the cardiac and respiratory components of IVC movement and pulsatility and evidenced the spatial dependence of IVC pulsatility. IVC tracking appears to be a promising approach to reduce movement artifacts and to improve the reliability of IVC diameter monitoring.

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The inferior vena cava (IVC) shows variations of cross-section over time (referred to as pulsatility) induced by different stimulations, like as breathing and heartbeats. The amplitude of these pulsations is affected by the volume status of the patient and can be investigated by ultrasound (US) mea

The echocardiographic estimation of right atrial pressure (RAP) is based on the size and inspiratory collapse of the inferior vena cava (IVC). However, this method has proven to have limits of reliability. The aim of this study is to assess feasibility and accuracy of a new semi-automated approach to estimate RAP. Standard acquired echocardiographic images were processed with a semi-automated technique. Indexes related to the collapsibility of the vessel during inspiration (Caval Index, CI) and new indexes of pulsatility, obtained considering only the stimulation due to either respiration (Respiratory Caval Index, RCI) or heartbeats (Cardiac Caval Index, CCI) were derived. Binary Tree Models (BTM) were then developed to estimate either 3 or 5 RAP classes (BTM3 and BTM5) using indexes estimated by the semi-automated technique. These BTMs were compared with two standard estimation (SE) echocardiographic methods, indicated as A and B, distinguishing among 3 and 5 RAP classes, respectively. Direct RAP measurements obtained during a right heart catheterization (RHC) were used as reference. 62 consecutive 'all-comers' patients that had a RHC were enrolled; 13 patients were excluded for technical reasons. Therefore 49 patients were included in this study (mean age 62.2 ± 15.2 years, 75.5% pulmonary hypertension, 34.7% severe left ventricular dysfunction and 51% right ventricular dysfunction). The SE methods showed poor accuracy for RAP estimation (method A: misclassification error, ME = 51%, R 2 = 0.22; method B: ME = 69%, R 2 = 0.26). Instead, the new semi-automated methods BTM3 and BTM5 have higher accuracy (ME = 14%, R 2 = 0.47 and ME = 22%, R 2 = 0.61, respectively). In conclusion, a multi-parametric approach using IVC indexes extracted by the semi-automated approach is a promising tool for a more accurate estimation of RAP.