Thoracic impedance measures tissue characteristics in the vicinity of the electrodes, not intervening lung water: implications for heart failure monitoring

Despite treatment advances and more intensive clinical monitoring, heart failure (HF) remains one of the most common causes for hospitalization and is associated with high morbidity, mortality and economic costs [1]. The increasing use of implantable cardioverter defibrillators (ICD) and cardiac resynchronization therapy (CRT) devices in patients with HF makes it possible to remotely monitor intrathoracic impedance (Z) in combination with other physiological parameters [2]. Z measurements using the right ventricular (RV) shocking coil to the device case vector (RV_coil-Case) are traditionally thought to represent the resistance to electrical flow across a field extending through the lungs, such that changes in Z can be interpreted to reflect changes in thoracic fluid volume and pulmonary congestion [3, 4]. Based on this premise several studies have shown that it is possible to use Z to predict and potentially reduce hospitalizations for acute decompensated HF (ADHF) [5, 6]. However, because of the limited specificity and sensitivity of Z monitoring when using the RV_coil-Case vector [5, 7], more recent studies have explored the use of alternative and combination vectors from CRT leads [8‐10].

Pre-clinical studies using multiple vectors have shown that each vector changes at a different rate and magnitude in response to the development of pacing-induced HF [9, 10]. The left ventricular (LV) ring electrode to device case vector (LV_ring-Case) demonstrated the fastest rate and greatest magnitude of change, and correlated well with left atrial pressure (LAP). A recent clinical study reported that a combination of Z vectors, rather than Z from a single vector can successfully identify increases in thoracic fluid volume that will culminate in ADHF. Using a combination vector from either CRT or ICD leads showed improved sensitivity and a lower false positive rate compared with the single RV_coil-Case vector [11].

In order to more effectively exploit the availability of Z from multiple vectors, we sought to gain better insight into what is being measured by these vectors. The electric current flowing between two electrodes forming a vector does not necessarily travel along a straight line across the lungs, but more likely along pathways of lesser resistance. We, therefore, hypothesized that the most significant contribution to the measured Z is from the electrode-tissue interface where there is high impedance to electrical flow, and that beyond this interface the contribution to the measured Z is negligible [12]. This is because beyond the electrode-tissue interface the current finds its way to flow through low resistance structures, such as blood vessels, that do not have a significant contribution to the measured Z. If Z primarily depends on the electrode-tissue interface, then it provides a measure of the local tissue characteristics surrounding the two electrodes rather than the characteristics of tissues located farther away between the electrodes. This new interpretation may help explain why recent clinical trials have shown that monitoring of Z has limited effectiveness in detecting ADHF [13, 14], particularly in the early months post-device implant when there are significant non-HF related changes occurring at the electrode-tissue interface. To test the hypothesis that Z primarily reflects local tissue characteristics we evaluated a new computational model for deriving the near-field impedance contributions from the various electrodes and conducted a pre-clinical experiment to illustrate how near-field impedances may be monitored at multiple sites.

The study protocol was approved by the Animal Ethics Committee of the University of Otago, Christchurch, New Zealand.

In this study we demonstrate for the first time that changes in vector-based Z measurements may readily develop in response to changes occurring at the electrode-tissue interface, thereby providing a possible mechanism that explains why Z monitoring has limited sensitivity and specificity in detecting ADHF [13]. The hypothesis that Z primarily reflects local tissue characteristics suggests that non-HF events, such as healing post-implant, lead migration/dislodgement, and device-pocket infection, can easily confound the interpretation of changes in Z measurements [4, 14]. Thus, in the current study we evaluated changes in both vector-based Z and Z_E responses during rapid changes in LAP induced by volume and non-volume-dependent mechanisms. Volume loading with dextran is a standard physiological model designed to acutely increase intravascular and intracardiac volumes [19, 20]. The rate and duration of dextran infusion in the current study was sufficient to increase intravascular and intracardiac volumes with an approximate 15 mmHg rise in LAP, but is unlikely to have caused pulmonary edema. Rapid ventricular pacing is a well established animal model of congestive HF which consistently induces significant sodium and water retention, changes in intracardiac volumes and pressures and pulmonary edema [17]. This model has been previously used in our lab to study vector-based impedance changes with the onset and offset of congestive HF, thereby modelling ADHF decompensation and recovery [10]. Results from the current study confirm that pacing induced HF not only reduces all vector-based impedances, as previously shown [10], but also consistently reduces Z_E derived from each of the electrodes.

Results from the current study support our hypothesis that Z primarily reflects local tissue characteristics by demonstrating that intrathoracic impedance measurements reflect the local tissue and fluid conditions surrounding each of the electrodes, rather than the characteristics of tissues located farther away in the region between the measuring electrodes. The highest near-field impedance (Z_E) was associated with the smaller-sized LV_ring, RV_ring and RA_ring electrodes which had greater resistance to electrical flow at the electrode-tissue interface (Table 1). The lowest Z_E was associated with the Case and RV_coil electrodes, consistent with these electrodes being larger in size with less resistance to electrical flow. The LV_ring electrode had the highest Z_E, consistent with this electrode being surrounded by more tissue and less blood.

To construct the mathematical model we hypothesized that the current flows along a pathway from the first electrode to the second electrode which includes three components; (1) the tissues adjacent to the first electrode; (2) the tissues and/or blood located farther away between the two electrodes; and (3) the tissues adjacent to the second electrode. The measured impedance between the first electrode and the second electrode therefore can be modelled as the summation of the impedance associated with each of these pathway components. We also hypothesized that the contribution to the measured impedance between the first and the second electrode is greatest from the 1st and 3rd components of the pathway, and that the contribution from the 2nd component is significantly lower such that it may be ignored. We believe this hypothesis to be correct because the electrical current will find its way to flow through a pathway between the electrodes that has the lowest impedance to electrical flow, such as along blood vessels. Thus, the mathematical model for the measured impedance between two electrodes was simplified to consist of only the 1st and 3rd components. Since we had six measurements of vector based impedance from five electrodes we were able to compute the contribution from the LV_ring electrode in more than one way (LV1 and LV2) which allowed us to verify our hypothesis that the impedance associated with the 2nd component pathway can be ignored.

The most striking example of impedance reflecting the local tissue and fluid conditions surrounding an electrode was seen in the device pocket edema study where, although vector-based Z (V1, V2, and V4) fell in response to the injection of fluid into the device pocket, near-field computation demonstrated that the marked and precipitous fall in the Case Z_E contributed most, if not all, to the decrease in the vector-based Z. This can be seen in Fig. 5a where the falls in Z for V1, V2, and V4 are plotted at 30 min following saline injection into the pocket. The reduction in Z for V1 and V4 is contributed almost exclusively by the fall in Z_E of the Case electrode, with little if any contribution from the Z_E of the LV_ring or RV_coil electrodes, respectively. The large accumulation of fluid surrounding the Case resulted in little discernable change in LAP or Z_E for any of the other implanted electrodes located far away from the device pocket. A similar response pattern in the measured Z is classically seen whenever a pulse generator is replaced, which results in the formation of local edema within the device pocket during the first 24 h, followed by the normal phases of tissue healing occurring over the subsequent weeks to months. Thus, device pocket edema induces significant reductions in the measured Z that may be falsely interpreted [4]. However, with the ability to remove the contribution of the Case electrode from the measured vector-based Z, it is possible to monitor impedance without it being subjected to otherwise confounding changes that are occurring within the device pocket.

The hypothesis that Z primarily reflects local tissue characteristics is further supported by the intravascular volume expansion studies performed both in normal (pre-pacing) and HF sheep which induced a significant increase in LAP that was promptly tracked by corresponding reductions in the Z_E measurements from the intra-cardiac (RV_ring, RA_ring and RV_coil) electrodes. The acute and the delayed responses to intravascular volume expansion in the normal (pre-pacing) sheep are illustrated in Fig. 5b and c, respectively. At 30 min following commencement of volume expansion, which corresponds to the time when LAP first peaked, there is a dramatic fall in Z for V2 and V4, whereas for V1 there is a slight unexpected increase (Fig. 5b). Near-field computation demonstrates that the acute reduction in Z for V2 and V4 is contributed entirely by a fall in the Z_E for the RV_ring and RV_coil electrodes, respectively. Because the RV_ring and RV_coil electrodes are located within the RV chamber, a rapid increase in chamber volume causes more fluid to surround the electrodes and less tissue to be in contact with the electrodes, such that the near-field contribution to the measured vector-based Z is proportionally reduced.

Following the 30 min time point the Z for V1 has a steady decrease (Fig. 2), which is occurring over the time period when the infused fluid is being redistributed to other compartments. At the 300 min time point (Fig. 5c) near-field computation demonstrates that virtually all of the reduction in Z for V1 is contributed by the fall in the Z_E for the LV_ring electrode. Although the LV_ring electrode is implanted within an epicardial blood vessel, its delayed response suggests that the LV_ring electrode is not in direct communication with the RV blood pool. This may be secondary to possible formation of scar tissue within the distal coronary venous implant site (confirmed by autopsy in some animals) causing obstruction to blood flow. Importantly, Z_E from the LV_ring electrode was found to be sensitive to congestion within the adjacent epicardial fat, as demonstrated post volume expansion in canine studies in our lab (unpublished observations), and to pericardial fluid volume and the degree of contact between the LV_ring electrode and the pericardial sac [21]. Thus, an increase in the degree of tissue contact between the LV_ring electrode and the pericardial sac as a consequence of an expanding cardiac chamber volume may explain the unexpected initial increase observed in response to acute volume infusion, while the later development of epicardial fat edema may explain the delayed response. A change in the degree of contact between the LV_ring electrode and the pericardial sac may also occur in response to changes in posture or pericardial fluid volume irrespective of pulmonary congestion, and may result in false interpretations of the measured impedance as previously reported [21]. However, the influence of free flowing pericardial fluid volume and posture may be less critical in patients with a scarred pericardial space following open heart surgery, or an episode of pericarditis.

There were variations in the recovery pattern of the measured Z_E following cessation of volume loading that depended on the electrode implant location. All five electrodes had a much slower recovery rate in Z_E (>12 h) compared to LAP (~3 h). The intra-cardiac right-sided electrodes demonstrated a faster recovery compared to the LV_ring and Case electrodes. The delay in recovery of impedance in comparison to LAP is consistent with previous reported findings [10], and is likely a consequence of the longer time required to restore the local fluid volume conditions surrounding the various electrodes, particularly when located outside the intravascular space. Similarly, termination of rapid ventricular pacing caused a precipitous acute fall in LAP, followed by a gradual recovery over the subsequent 12 h. This was in contrast to the significantly slower recovery seen in Z_E (~3 days—data not shown), which is consistent with previously reported data for Z_V [10]. The lag seen between Z_E and LAP is likely a consequence of Z_E being more a reflection of the local volume and corresponding tissue contact rather than pressure.

Taken together, the results of the present study validate the computational model used to derive the near-field impedances (Z_E), and demonstrate that vector-based Z primarily depends on the impedance from the tissues in the vicinity of the measuring electrodes, and therefore, reflects local tissue characteristics. This finding may explain why vector-based Z can display changes that do not coincide with pulmonary congestion, particularly in the early months post-implant when there are significant changes occurring at the electrode-tissue interface. This is consistent with the results from a recent clinical trial which demonstrate that the positive predictive value of a Z monitoring algorithm is particularly low in the initial 6 months post-implant, but subsequently improves over time [13]. Instabilities post-implant are more likely to occur with Z that are associated with a passive fixation lead, such as an LV pacing lead, where there is a greater chance for a micro-dislodgement to occur (Fig. 6). Therefore, it may be preferable to allow more time for the electrode-tissue interface to stabilize before relying on Z measurements for clinical decision making, or to rely on Z vectors that are derived from an active fixation lead (RV_coil-Case and RV_ring-Case). Once the electrode-tissue interface is stabilized, this study demonstrates that the Z_E associated with the intra-cardiac electrodes (RV_ring, RA_ring, and RV_coil) respond faster than the Z_E associated with the LV_ring and Case electrode to an expanding intra-cardiac chamber volume. The Z_E associated with the LV_ring and Case electrodes are additionally influenced by changes occurring within the pericardial space or device pocket, which may not coincide with pulmonary congestion. Therefore, relying on the Z_E associated with the intra-cardiac electrodes for clinical decision-making may be more advantageous than other electrodes or Z vectors.

We have reported for the first time a validated method for determining the relative contributions to the measured vector-based impedance from the various electrodes, and have demonstrated that vector-based impedance measurements predominantly reflect physical phenomena occurring in the vicinity of the measuring electrodes rather than farther away within the pulmonary parenchyma. Thus, the near-field computational model offers a new paradigm for examining impedance data from multi-lead devices which may prove clinically-useful in monitoring changes at specific anatomical locations in close proximity to the individual recording electrodes. The results of this study help explain why vector-based impedance measurements may display changes that do not necessarily correlate with the presence of pulmonary congestion, and support the hypothesis that intrathoracic impedance actually measures local tissue characteristics rather than intervening lung water.