Medical Engineering and Physics 38 (2016) 538–546 Contents lists available at ScienceDirect Medical Engineering and Physics journal homepage: www.elsevier.com/locate/medengphy A method to adapt thoracic impedance based on chest geometry and composition to assess congestion in heart failure patients Illapha Cuba-Gyllensten a,b,∗ , Paloma Gastelurrutia c , Alberto G. Bonomi a , Jarno Riistama a , Antoni Bayes-Genis c,d , Ronald M. Aarts a,b a Department of Chronic Disease Management, Philips Research, Eindhoven, the Netherlands b Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands c ICREC Research Program, Fundació Institut d’Investigació en Ciències de la Salut Germans Trias i Pujol (IGTP), Badalona, Spain d Department of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain a r t i c l e i n f o Article history: Received 13 May 2015 Revised 18 January 2016 Accepted 6 March 2016 Keywords: Heart failure Bioimpedance spectroscopy Personalization Simulation Decompensation a b s t r a c t 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 cir- cumference, 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 volun- teers 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 measure- ments 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. © 2016 IPEM. Published by Elsevier Ltd. All rights reserved. 1. Introduction Congestion is a defining feature of decompensated heart fail- ure (HF), a frequent cause for hospitalization, and a main target during treatment [1]. Despite this, there is a paucity of tools that provide a quantified assessment of the level of congestion. Cur- rent tools are often complex requiring invasive measurements to establish heamodynamic pressures or chest x-rays which exposes the patient to ionizing radiation and give equivocal results. Clinical judgment on the other hand is often inexact and requires substan- tial clinical acumen [2]. Preferably methods that establish conges- tion should be simple and easy to use with reliable results. Trans-thoracic bioimpedance (TTI) can be used to assess tis- sue hydration as increased fluid levels increase the conductivity of the tissue. This has been used to show that non-invasive measure- ∗ Corresponding author at: Department of Personal Health Solutions, Philips Re- search, Eindhoven, the Netherlands. Tel.: +31 631 926 930. E-mail address: illapha@gmail.com (I. Cuba-Gyllensten). ments of impedance at a single frequency correlates with radio- graphic and clinical indices of pulmonary oedema in HF patients [3,4]. Different frequencies have different progressions [5] and multi-frequency measurements can be used to improve estimates of body fluids by modeling the spectroscopic response [6]. For liv- ing biological tissues measured in the kilohertz to megahertz range this response, β dispersion, can be approximated by a Cole model [7]. This empirical model describes the impedance based on four variables: R 0 , the extrapolated zero frequency or DC component; R ∞ , the extrapolated infinite frequency component; f C , the charac- teristic frequency; and α, the dispersion parameter [8]. At low fre- quencies the resistance is impacted by the extra-cellular fluids to a larger extent than at higher frequencies, for which a larger part of the current passes through the cell membranes. Increased fluids in the lung interstitium and later into the alveoli should thus be reflected in the DC component of the model, R 0 . A challenge with bioimpedance measures is that the individual optimal value depends on the morphology and distribution of the different tissues. Without a target value one can only establish rel- ative changes in fluid levels which can be difficult to interpret and http://dx.doi.org/10.1016/j.medengphy.2016.03.002 1350-4533/© 2016 IPEM. Published by Elsevier Ltd. All rights reserved.