BACKGROUND/AIMS: Recently, ultrasound signals termed 'lung water comets' associated with pulmonary edema have been correlated with adverse clinical events in dialysis patients. These comets fluctuate substantially during the ultrasound exam highlighting the need for objective quantitative measurement methods. METHODS: We developed an image-processing algorithm for the detection and quantification of lung comets. Quantification measures included comet number (comet count) and the fraction of the ultrasound beams with comet findings (comet fraction). We used this algorithm in a pilot study in 20 stable dialysis outpatients to identify associations between ultrasound comets and clinical parameters including blood pressure (BP), percent blood volume reduction on dialysis (%BV), ejection fraction (EF), and ultrafiltration on dialysis (UF). RESULTS: Positive findings included associations with lung comet measurements with pre-dialysis Diastolic BP (r = 0.534, p = 0.015), subject age (r = -0.446, p = 0.049), and a combination of EF and end dialysis %BV reduction (r = -0.585, p = 0.028). Comet fraction and comet count were closely correlated due to the inherent relationship between these two metrics (r = 0.973, p < 0.001). Negative findings included ultrasound comets that did not change from beginning to end of dialysis (p = 0.756), and were not significantly correlated with single dialysis treatment UF (p = 0.522), subject body weight (p = 0.208), or BMI (p = 0.358). CONCLUSIONS: Ultrasound signal processing methods may help quantify lung ultrasound comets. Additional findings include algorithmic lung comet measurement that did not change significantly during single dialysis sessions in these stable outpatients, but were associated with cardiovascular and fluid status parameters.
BACKGROUND/AIMS: Recently, ultrasound signals termed 'lung water comets' associated with pulmonary edema have been correlated with adverse clinical events in dialysis patients. These comets fluctuate substantially during the ultrasound exam highlighting the need for objective quantitative measurement methods. METHODS: We developed an image-processing algorithm for the detection and quantification of lung comets. Quantification measures included comet number (comet count) and the fraction of the ultrasound beams with comet findings (comet fraction). We used this algorithm in a pilot study in 20 stable dialysis outpatients to identify associations between ultrasound comets and clinical parameters including blood pressure (BP), percent blood volume reduction on dialysis (%BV), ejection fraction (EF), and ultrafiltration on dialysis (UF). RESULTS: Positive findings included associations with lung comet measurements with pre-dialysis Diastolic BP (r = 0.534, p = 0.015), subject age (r = -0.446, p = 0.049), and a combination of EF and end dialysis %BV reduction (r = -0.585, p = 0.028). Comet fraction and comet count were closely correlated due to the inherent relationship between these two metrics (r = 0.973, p < 0.001). Negative findings included ultrasound comets that did not change from beginning to end of dialysis (p = 0.756), and were not significantly correlated with single dialysis treatment UF (p = 0.522), subject body weight (p = 0.208), or BMI (p = 0.358). CONCLUSIONS: Ultrasound signal processing methods may help quantify lung ultrasound comets. Additional findings include algorithmic lung comet measurement that did not change significantly during single dialysis sessions in these stable outpatients, but were associated with cardiovascular and fluid status parameters.