title: A method to adapt thoracic impedance based on chest geometry and composition to assess congestion in heart failure patients.
abstract: Multi-frequency trans-thoracic bioimpedance (TTI) could be used to track fluid changes and congestion of the lungs, however, patient specific characteristics may impact the measurements. We investigated the effects of thoracic geometry and composition on measurements of TTI and developed an equation to calculate a personalized fluid index. Simulations of TTI measurements for varying levels of chest circumference, fat and muscle proportion were used to derive parameters for a model predicting expected values of TTI. This model was then adapted to measurements from a control group of 36 healthy volunteers to predict TTI and lung fluids (fluid index). Twenty heart failure (HF) patients treated for acute HF were then used to compare the changes in the personalized fluid index to symptoms of HF and predicted TTI to measurements at hospital discharge. All the derived body characteristics affected the TTI measurements in healthy volunteers and together the model predicted the measured TTI with 8.9% mean absolute error. In HF patients the estimated TTI correlated well with the discharged TTI (r=0.73,p <0.001) and the personalized fluid index followed changes in symptom levels during treatment. However, 37% (n=7) of the patients were discharged well below the model expected value. Accounting for chest geometry and composition might help in interpreting TTI measurements.
authors.affiliation: Department of Chronic Disease Management, Philips Research, Eindhoven, the Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands. Electronic address: illapha@gmail.com.
authors.forename: Illapha
authors.initials: I
authors.lastname: Cuba-Gyllensten
authors.affiliation: ICREC Research Program, Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol (IGTP), Badalona, Spain.
authors.forename: Paloma
authors.initials: P
authors.lastname: Gastelurrutia
authors.affiliation: Department of Chronic Disease Management, Philips Research, Eindhoven, the Netherlands.
authors.forename: Alberto G
authors.initials: AG
authors.lastname: Bonomi
authors.affiliation: Department of Chronic Disease Management, Philips Research, Eindhoven, the Netherlands.
authors.forename: Jarno
authors.initials: J
authors.lastname: Riistama
authors.affiliation: ICREC Research Program, Fundació Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol (IGTP), Badalona, Spain; Department of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain.
authors.forename: Antoni
authors.initials: A
authors.lastname: Bayes-Genis
authors.affiliation: Department of Chronic Disease Management, Philips Research, Eindhoven, the Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.
authors.forename: Ronald M
authors.initials: RM
authors.lastname: Aarts
keywords: Bioimpedance spectroscopy; Decompensation; Heart failure; Personalization; Simulation