Regional lung perfusion as determined by electrical impedance tomography in comparison with electron beam CT imaging

Measurement of ventilation and cardiac related impedance changes with electrical impedance tomography

INTRODUCTION

Electrical impedance tomography (EIT) has been shown to be able to distinguish both ventilation and perfusion. With adequate filtering the regional distributions of both ventilation and perfusion and their relationships could be analysed. Several methods of separation have been suggested previously, including breath holding, electrocardiograph (ECG) gating and frequency filtering. Many of these methods require interventions inappropriate in a clinical setting. This study therefore aims to extend a previously reported frequency filtering technique to a spontaneously breathing cohort and assess the regional distributions of ventilation and perfusion and their relationship.

METHODS

Ten healthy adults were measured during a breath hold and while spontaneously breathing in supine, prone, left and right lateral positions. EIT data were analysed with and without filtering at the respiratory and heart rate. Profiles of ventilation, perfusion and ventilation/perfusion related impedance change were generated and regions of ventilation and pulmonary perfusion were identified and compared.

RESULTS

Analysis of the filtration technique demonstrated its ability to separate the ventilation and cardiac related impedance signals without negative impact. It was, therefore, deemed suitable for use in this spontaneously breathing cohort.Regional distributions of ventilation, perfusion and the combined ΔZV/ΔZQ were calculated along the gravity axis and anatomically in each position. Along the gravity axis, gravity dependence was seen only in the lateral positions in ventilation distribution, with the dependent lung being better ventilated regardless of position. This gravity dependence was not seen in perfusion.When looking anatomically, differences were only apparent in the lateral positions. The lateral position ventilation distributions showed a difference in the left lung, with the right lung maintaining a similar distribution in both lateral positions. This is likely caused by more pronounced anatomical changes in the left lung when changing positions.

CONCLUSIONS

The modified filtration technique was demonstrated to be effective in separating the ventilation and perfusion signals in spontaneously breathing subjects. Gravity dependence was seen only in ventilation distribution in the left lung in lateral positions, suggesting gravity based shifts in anatomical structures. Gravity dependence was not seen in any perfusion distributions.

Electrical impedance tomography compared to positron emission tomography for the measurement of regional lung ventilation: an experimental study

Introduction

Electrical impedance tomography (EIT), which can assess regional lung ventilation at the bedside, has never been compared with positron-emission tomography (PET), a gold-standard to quantify regional ventilation. This experiment systematically compared both techniques in injured and non-injured lungs.

Methods

The study was performed in six mechanically ventilated female piglets. In normal lungs, tidal volume (V_T) was randomly changed to 6, 8, 10 and 15 ml/kg on zero end-expiratory pressure (ZEEP), then, at V_T 10 ml/kg, positive end-expiratory pressure (PEEP) was randomly changed to 5, 10 and 15 cmH₂O. Afterwards, acute lung injury (ALI) was subsequently created in three animals by injecting 3 ml/kg hydrochloric acid into the trachea. Then at PEEP 5 cmH₂O, V_T was randomly changed to 8 and 12 ml/kg and PEEP of 10 and 15 cmH₂O applied at V_T 10 ml/kg. EIT and PET examinations were performed simultaneously. EIT ventilation (V_TEIT) and lung volume (V_L) were measured in the anterior and posterior area of each lung. On the same regions of interest, ventilation (V_PET) and aerated lung volume (VA_atten) were determined with PET.

Results

On ZEEP, V_TEIT and V_PET significantly correlated for global (V_TEIT = VPET - 2E-13, R² = 0.95, P < 0.001) and regional (V_TEIT = 0.81V_PET+7.65, R² = 0.63, P < 0.001) ventilation over both conditions. For ALI condition, corresponding R² were 0.91 and 0.73 (P < 0.01). Bias was = 0 and limits of agreement were -37.42 and +37.42 ml/min for global ventilation over both conditions. These values were 0.04 and -29.01 and +29.08 ml/min, respectively, for regional ventilation. Significant correlations were also found between V_L and VA_atten for global (V_L = VA_atten+1E-12, R² = 0.93, P < 0.0001) and regional (V_L = 0.99VA_atten+0.92, R² = 0.65, P < 0.001) volume. For ALI condition, corresponding R² were 0.94 (P < 0.001) and 0.54 (P < 0.05). Bias was = 0 and limits of agreement ranged -38.16 and +38.16 ml for global ventilation over both conditions. These values were -0.24 and -31.96 to +31.48 ml, respectively, for regional ventilation.

Conclusions

Regional lung ventilation and volume were accurately measured with EIT in healthy and injured lungs and validated by simultaneous PET imaging.

Electrical impedance tomography applied to assess matching of pulmonary ventilation and perfusion in a porcine experimental model

INTRODUCTION

Electrical impedance tomography (EIT) can be used to measure impedance changes related to the thoracic content of air and blood. Few studies, however, have utilised EIT to make concurrent measurements of ventilation and perfusion. This experimental study was performed to investigate the feasibility of EIT to describe ventilation/perfusion (V/Q) matching after acute changes of pulmonary perfusion and aeration.

METHODS

Six mechanically ventilated, anaesthetised pigs in the supine position were studied at baseline, after inflation of a balloon in the inferior caval vein (Binfl) to reduce cardiac output and after an increased positive end-expiratory pressure (PEEP) of 20 cmH2O (PEEP20) to increase pulmonary aeration. EIT measurements were performed at the mid-thoracic level to measure the amplitude of impedance changes related to ventilation (ZV) and perfusion (ZQ), both globally and in four defined regions of interest (ROI) extending from the ventral to dorsal distance.

RESULTS

A largely parallel distribution of ZV and ZQ in all four ROIs during baseline conditions corresponded to a bell-shaped frequency distribution of ZV/ZQ ratios with only moderate scatter. Binfl and PEEP20 with unchanged tidal volumes significantly increased the mismatch of regional ZV and ZQ, the scatter of ZV/ZQ ratios and the heterogeneity of the ZV/ZQ frequency distribution. Significant positive and negative correlations were demonstrated between fractional alveolar dead space (r2 = 0.63 [regression coefficient]) and venous admixture (r2 = 0.48), respectively, and the global ZV/ZQ ratio.

CONCLUSIONS

EIT may be used to monitor the distribution of pulmonary ventilation and perfusion making detailed studies of V/Q matching possible.

Performance of electrical impedance tomography in detecting regional tidal volumes during one-lung ventilation

BACKGROUND

Electrical impedance tomography (EIT) is becoming a new medical imaging modality for continuous monitoring of regional lung function in the intensive care unit or operating room. The aim of our study was to evaluate the performance of EIT in detecting regional tidal volumes in patients during volume-controlled mechanical ventilation of one or both lungs.

METHODS

Ten adult patients undergoing elective thoracic surgery were included. EIT measurements were performed with the Goe-MF II EIT system. Data were collected before surgery during ventilation of both, the right and left lungs. Tidal volumes of 800 and 400 ml were applied during bilateral and unilateral ventilation, respectively.

RESULTS

Ventilation-related impedance changes determined in the whole chest cross-section during the right and left lung ventilation did not significantly differ from each other and were equal to 47.6+/-5.6% and 48.5+/-7.8% (mean+/-SD) of the value determined during bilateral ventilation. During unilateral ventilation, EIT clearly separated the ventilated and non-ventilated lung regions; nevertheless, ventilation-related impedance changes were also detected at the non-ventilated sides in areas corresponding to 3.4+/-4.1% and 12.4+/-6.9% of the scan halves during ventilation of the left and right lung, respectively. Changes in global tidal volumes were adequately detected by EIT during both bilateral and unilateral lung ventilation.

CONCLUSION

Although good separation of the ventilated and non-ventilated sides of the chest was possible, the data indicate that reliable quantification of regional tidal volumes during asymmetric or inhomogeneous distribution patterns requires regions-of-interest analysis.

Dynamic separation of pulmonary and cardiac changes in electrical impedance tomography

In spontaneously breathing or ventilated subjects, it is difficult to image cardiac-related conductivity changes using electrical impedance tomography (EIT) due to the high amplitude of the ventilation component. Previous attempts to separate these components included either electrocardiogram-gated averaging, frequency domain filtering or holding the breath while performing the measurements. However, such methods are either not able to produce continuous real-time images or to fully separate cardiac and pulmonary changes. The aim of this work was to develop a new dynamic filtering method for the online separation of pulmonary and cardiac changes avoiding the drawbacks of the previous attempts. The approach is based on estimating template functions for the pulmonary and cardiac components by means of principal component analysis and frequency domain filtering. Then, these templates are fitted into the input signals. The new method enables an observer to examine the variation of the cardiac signal beat-by-beat after a one-time setup period of 20 s. Preliminary in vivo results of two healthy subjects are presented. The results are superior to frequency domain filtering and in good agreement with signals averaged over several cardiac cycles. The method does not depend on ECG or other a priori knowledge. The apparent validity of the method's ability to separate cardiac and pulmonary changes in EIT images was shown and has to be confirmed in future studies. The algorithm opens up new possibilities for future clinical trials on continuous monitoring by means of EIT and for the examination of the relation between the cardiac component and lung perfusion.

Fuzzy modeling of electrical impedance tomography images of the lungs

OBJECTIVES

Aiming to improve the anatomical resolution of electrical impedance tomography images, we developed a fuzzy model based on electrical impedance tomography's high temporal resolution and on the functional pulmonary signals of perfusion and ventilation.

INTRODUCTION

Electrical impedance tomography images carry information about both ventilation and perfusion. However, these images are difficult to interpret because of insufficient anatomical resolution, such that it becomes almost impossible to distinguish the heart from the lungs.

METHODS

Electrical impedance tomography data from an experimental animal model were collected during normal ventilation and apnea while an injection of hypertonic saline was administered. The fuzzy model was elaborated in three parts: a modeling of the heart, the pulmonary ventilation map and the pulmonary perfusion map. Image segmentation was performed using a threshold method, and a ventilation/perfusion map was generated.

RESULTS

Electrical impedance tomography images treated by the fuzzy model were compared with the hypertonic saline injection method and computed tomography scan images, presenting good results. The average accuracy index was 0.80 when comparing the fuzzy modeled lung maps and the computed tomography scan lung mask. The average ROC curve area comparing a saline injection image and a fuzzy modeled pulmonary perfusion image was 0.77.

DISCUSSION

The innovative aspects of our work are the use of temporal information for the delineation of the heart structure and the use of two pulmonary functions for lung structure delineation. However, robustness of the method should be tested for the imaging of abnormal lung conditions.

CONCLUSIONS

These results showed the adequacy of the fuzzy approach in treating the anatomical resolution uncertainties in electrical impedance tomography images.

[Electrical impedance tomography: ready for routine clinical use for mechanically ventilated patients?]

Electrical impedance tomography (EIT) is a non-invasive, radiation-free functional imaging technique, which offers the possibility of continuous bedside measurement of regional lung ventilation. The principle of EIT is based on the input of alternating current and voltage measurement via surface electrodes placed around the thorax, which measure changes of electrical impedance parallel to changes in aeration within the lungs. This enables the measurement of regional ventilation. Because of the rapid time resolution of this technique, it can be used for the measurement of fast physiological effects. For more than 20 years EIT has been intensively used for research purposes, but has not yet been used for the monitoring of regional lung function in the routine clinical setting. This review describes the status of EIT in the clinical routine, its possibilities and limitations.

Imaging cardiac activity by the D-bar method for electrical impedance tomography

A practical D-bar algorithm for reconstructing conductivity changes from EIT data taken on electrodes in a 2D geometry is described. The algorithm is based on the global uniqueness proof of Nachman (1996 Ann. Math. 143 71-96) for the 2D inverse conductivity problem. Results are shown for reconstructions from data collected on electrodes placed around the circumference of a human chest to reconstruct a 2D cross-section of the torso. The images show changes in conductivity during a cardiac cycle.

A parametric model of the relationship between EIT and total lung volume

Spirometry and electrical impedance tomography (EIT) data from 26 healthy subjects (14 males, 12 females) were used to develop a model linking contrast variations in EIT difference images to lung volume changes. Eight recordings, each 64 s long, were made for each subject in four postures (standing, sitting, reclining at 45 degrees, supine) and two breathing modes (quiet tidal and deep breathing). Age, gender and five anthropometric variables were recorded. The database was divided into four subsets. The first subset, data from 22 subjects (12 males, 10 females) recorded in deep breathing mode, was used to create the model. Validation was done with the other subsets: data recorded during quiet tidal breathing in the same 22 subjects, and data recorded in both breathing modes for the other four subjects. A quadratic equation in DeltaV(P) (lung volume changes recorded by the spirometer) provided a very good fit to total contrast changes in the EIT images. The model coefficients were found to depend on posture, gender, thoracic circumference and scapular skin fold. To validate the model, the quadratic equation was inverted to estimate lung volume changes from the EIT images. The estimated changes were then compared to the measured volume changes. Validations with each data subset yielded mean standard errors ranging from 9.3% to 12.4%. The proposed model is a first step in enabling inter individual comparisons of EIT images since: (1) it provides a framework for incorporating the effects of anthropometric variables, gender and posture, and (2) it references the images to a physical quantity (volume) verifiable by spirometry.

Determinants of pulmonary perfusion measured by electrical impedance tomography

Electrical impedance tomography (EIT) is a non-invasive imaging technique for detecting blood volume changes that can visualize pulmonary perfusion. The two studies reported here tested the hypothesis that the size of the pulmonary microvascular bed, rather than stroke volume (SV), determines the EIT signal. In the first study, the impedance changes relating to the maximal pulmonary pulsatile blood volume during systole (Delta Z(sys)) were measured in ten healthy subjects, ten patients diagnosed with chronic obstructive pulmonary disease, who were considered to have a reduced pulmonary vascular bed, and ten heart failure patients with an assumed low cardiac output but with a normal lung parenchyma. Mean Delta Z(sys) (SD) in these groups was 261 (34)x10(-5), 196 (39)x10(-5) ( P<0.001) and 233 (61)x10(-5) arbitrary units (AU) (P=NS), respectively. In the second study, including seven healthy volunteers, Delta Z(sys) was measured at rest and during exercise on a recumbent bicycle while SV was measured by means of magnetic resonance imaging. The Delta Z(sys) at rest was 352 (53)x10(-5 ) and 345 (112)x10(-5 )AU during exercise (P=NS), whereas SV increased from 83 (21) to 105 (34) ml (P<0.05). The EIT signal likely reflects the size of the pulmonary microvascular bed, since neither a low cardiac output nor a change in SV of the heart appear to influence EIT.

Markov chain Monte Carlo techniques and spatial–temporal modelling for medical EIT

Many imaging problems such as imaging with electrical impedance tomography (EIT) can be shown to be inverse problems: that is either there is no unique solution or the solution does not depend continuously on the data. As a consequence solution of inverse problems based on measured data alone is unstable, particularly if the mapping between the solution distribution and the measurements is also nonlinear as in EIT. To deliver a practical stable solution, it is necessary to make considerable use of prior information or regularization techniques. The role of a Bayesian approach is therefore of fundamental importance, especially when coupled with Markov chain Monte Carlo (MCMC) sampling to provide information about solution behaviour. Spatial smoothing is a commonly used approach to regularization. In the human thorax EIT example considered here nonlinearity increases the difficulty of imaging, using only boundary data, leading to reconstructions which are often rather too smooth. In particular, in medical imaging the resistivity distribution usually contains substantial jumps at the boundaries of different anatomical regions. With spatial smoothing these boundaries can be masked by blurring. This paper focuses on the medical application of EIT to monitor lung and cardiac function and uses explicit geometric information regarding anatomical structure and incorporates temporal correlation. Some simple properties are assumed known, or at least reliably estimated from separate studies, whereas others are estimated from the voltage measurements. This structural formulation will also allow direct estimation of clinically important quantities, such as ejection fraction and residual capacity, along with assessment of precision.