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Bedside Breath-Wise Visualization of Bronchospasm by Electrical Impedance Tomography Could Improve Perioperative Patient Safety: A Case Report

de la Oliva, Pedro MD, PhD*†; Waldmann, Andreas D. MSc; Böhm, Stephan H. MD; Verdú-Sánchez, Cristina MD*; Pérez-Ferrer, Antonio MD, PhD§; Alvarez-Rojas, Elena MD*

doi: 10.1213/XAA.0000000000000499
Case Reports: Case Report

Bronchospasm appears in up to 4% of patients with obstructive lung disease or respiratory infection undergoing general anesthesia. Clinical examination alone may miss bronchospasm. As a consequence, subsequent (mis)treatment and ventilator settings could lead to pulmonary hyperinflation, hypoxia, hypercapnia, hypotension, patient–ventilator asynchrony, volutrauma, or barotrauma. Electrical impedance tomography (EIT), a new noninvasive technique, can potentially identify bronchospasms by determining regional expiratory time constants (τ) for each one of the pixels of a functional EIT image. We present the first clinical case that highlights the potential of breath-wise EIT-based τ images of the lung to quickly identify bronchospasm at the bedside, which could improve perioperative patient management and safety.

From the *Pediatric Intensive Care Unit, Hospital Universitario La Paz, Madrid, ES, Spain; Department of Pediatrics, Medical School, Universidad Autónoma de Madrid, ES, Spain; Swisstom AG, Medical Research, Landquart, CH, Switzerland; and §Pediatric Anestesia and Reanimation Unit, Hospital Universitario La Paz, Madrid, ES, Spain.

Accepted for publication December 14, 2016.

Funding: None.

Conflicts of Interest: See Disclosures at the end of the article.

Address correspondence to Dr Pedro de la Oliva, UCIP, Hospital Materno-Infantil La Paz, Paseo de la Castellana, 261, 28046 Madrid, Spain. Address e-mail to

Bronchospasm is the common feature of reactive airway disease. Patients with bronchial asthma and chronic obstructive pulmonary disease show hyperreactive airway responses to mechanical and chemical irritants. The overall incidence of bronchospasm during general anesthesia in children younger than 10 years is approximately 0.2% and 0.4%. In patients with obstructive lung disease or respiratory infection, the incidence is 2% and 4%, respectively.1 During the perioperative period, bronchospasm may result from general anesthesia, hyperreactive airways, anaphylaxis, inadvertent extubation, pulmonary infections, or asthma. Untreated it can lead to pulmonary hyperinflation, hypoxia, hypercapnia, hypotension, patient–ventilator asynchrony, volutrauma, and barotrauma. Therefore, suspected bronchospasm should be confirmed and treated promptly.2

Under mechanical ventilation, bronchospasm usually manifests as expiratory wheeze, prolonged expiration, and/or increased inflation pressures.2 However, in severe bronchospasm, wheezes may be faint or even absent, thereby limiting their clinical identification, or may result from other critical conditions, for example, partial obstruction of the tracheal tube, pulmonary edema, aspiration, pulmonary embolism, tension pneumothorax, and airway secretions. In addition, increased peak airway pressure during volume control ventilation may have an origin other than bronchospasm.2 Accordingly, clinical examination may miss bronchospasm and thus delay treatment, especially in patients under mechanical ventilation.

Because passive inspiration and expiration follow exponential functions, the rate of volume change can be described by time constant (τ) determined as the product of compliance and resistance. After 3 • τ, inspiration or expiration is expected to be 95% completed. Because bronchospasm is characterized by reduced airway diameters causing a rise in the resistance to air flow, the measurement of τ may be useful for confirming the diagnosis and optimizing ventilator settings.3,4 For instance, during exhalation, shortening expiratory time <3 • τ may lead to air trapping, alveolar hyperinflation, or auto-positive end-expiratory pressure.4,5

Currently, τ can be estimated in patients under controlled passive positive pressure ventilation (PPV) from the passive exhalation flow–time and volume–time curves or under passive constant flow inflation from the calculation of the compliance and resistance of the respiratory system.6 Such numeric methods are inaccurate because they treat the lung as a single compartment and both chest wall compliance and tissue viscoelasticity are contained in the compliance and resistance’s measurement, respectively. In addition, in heterogeneous lungs, such numeric methods may overlook regions with significantly elevated τ that may result in mistreatment, volutrauma, and atelectasis.7

Electrical impedance tomography (EIT) is a noninvasive medical imaging technique that generates images of impedance distribution within the lungs from surface electrode measurements. Recently, we showed that EIT can be used to determine global as well as regional expiratory time constants (τ) and to clearly distinguish normal lungs from those with acute respiratory distress syndrome and chronic obstructive pulmonary disease.8 To date, however, images of regional τ have not been shown for acute episodes of bronchospasm.

The present case shows the potential application of breath-wise EIT-τ images to quickly identify bronchospasm at the bedside as well as to adjust and monitor treatment and ventilator settings to improve perioperative patient safety and management. Written consent was obtained from child’s parents to publish this case report.

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A 16-month-old former preterm boy with left pulmonary agenesis and bronchopulmonary dysplasia (BPD) required living donor liver transplantation for secondary biliary cirrhosis. The concurrence of major and lengthy surgery, pulmonary agenesis, and BPD led the medical–surgical team to request additional perioperative respiratory monitoring. Written informed consent from the parents was obtained to use a modified adult EIT monitor using a customized textile belt and a computed tomography-based patient-specific 3-dimensional chest model (Swisstom, Landquart, Switzerland; Figure 1).

Figure 1.

Figure 1.

Because the EIT monitor had not incorporated τ analysis yet, it was performed after the pediatric intensive care unit stay. In the present case, we created breath-wise τ-EIT images during a clinically suspected bronchospasm episode (Figure 1B). The temporal behavior of each lung’s pixel was determined by a nonlinear least square fitting of an exponential curve to data points between the time when 25% of its maximum amplitude was expired and the end of global expiration.9,10

In addition, we determined the center of ventilation (CoV) expressed as the percentage of the anteroposterior extension of the identified lung region where 0% refers to ventilation occurring in the most ventral and 100% in the most dorsal part of the lung.11

A baseline EIT recording was obtained 2 weeks before the surgery during a hospitalization for an episode of bronchospasm requiring supplemental nasal oxygen (Figure 1B, 1). Liver transplantation was postponed until the child had been off oxygen for more than a week.

The 10-hour surgery and the initial pediatric intensive care unit stay were uneventful (Figure 1B, 2). Weaning on pressure support ventilation 8 hours after surgery was accompanied by agitation, patient–ventilator asynchrony, wheezing and long exhalation times on auscultation, decreased Pao2, and increased Paco2 (Figure 1B, 3). Radiography showed no obvious alterations (Figure 1A). Based on clinical examination, patient history, and the high prevalence of bronchial hyperreactivity in BPD,12,13 bronchospasm was suspected.

Because of ongoing patient agitation, significant patient–ventilator asynchrony, nighttime, and recent surgery, the child was sedated and switched back to controlled ventilation for an additional 4 hours. Suctioning retrieved little secretions. Airway suctioning and aerosolized salbutamol were administered (Figure 1B, 4). To potentially alleviate the effects of strong suctioning, a short 3-minute recruitment maneuver was applied increasing positive end-expiratory pressure stepwise from 6 to 14 cm H2O and back.

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Tau images (Figure 1B, 1 and 3) reveal lung areas with long τ correlating with the respective clinical manifestations of bronchospasm in this child. In addition, these EIT-τ images identified regional differences in τ throughout the child’s lung. The changing distribution patterns of τ along the time and in response to bronchodilators are indicators of the τ’s functional nature and origin within the small airways and thus support the usefulness of EIT-τ to diagnose bronchospasm in the clinical settings of airway hyperresponsiveness.

The shift of the CoV toward the dorsal lung and the longer τ units in the nondependent lung are indicative of ventral lung hyperinflation during the bronchospasmic episode 2 weeks before surgery (Figure 1B, 1). The shift of the CoV toward the ventral lung seen shortly after surgery (Figure 1B, 2) with the patient still under control mechanical ventilation can be explained by anesthesia-induced atelectasis formation.14 In addition, the shortening of τ in the ventral area also contributed to the ventral CoV shift relative to the bronchospasmic episode before surgery (Figure 1B, 1).

During the second episode of bronchospasm (Figure 1B, 3), ventilation moved further ventrally as indicated by the upward movement of the CoV. This ventral predominance of ventilation can easily be explained by the corresponding longer τ in the dorsal dependent hypoventilated lungs. The dependent location of lung units with longer τ and the overinflated area during PPV (Figure 1B, 3) contrasts with the ventral nondependent distribution observed during the first episode of bronchospasm without PPV (Figure 1B, 1). Although we have not found any literature reference for such regional differences in τ distribution during PPV versus spontaneous breathing, they are consistent with physiology.15 The increase in resting volume in the ventral nondependent and therefore more compliant regions of the lung during PPV could have increased the radial traction on the airways, thereby reducing resistance and τ. On the other hand, a reduced resting volume and transmural pressure should be expected in the dorsal dependent regions during PPV. This would have lessened the radial traction of the surrounding lung tissue on the bronchi and aggravated the bronchospasm-induced reduction of airway caliber. As a result of the elevated τ in dorsal lung regions, air was trapped in the dependent areas during PPV (Figure 1B, 3).

Figure 1B, 4 shows a remarkably homogeneous shortening of τ after treatment with salbutamol, bronchial suctioning, sedation, and muscle relaxation while the CoV moved closer to its target location. τ images after the recruitment maneuver are essentially the same as that in Figure 1B, 4.

Although the clinical diagnosis and treatment were accurate, as was demonstrated by EIT-τ images, the pediatric intensivist in charge assumed some lung collapse induced by the suctioning, which, along with the absence of an accurate method to confirm the diagnosis of bronchospasm at the bedside, made her perform a short recruitment maneuver that could have triggered hyperinflation and barotrauma. Posttreatment EIT-τ images demonstrated that such recruitment maneuver did not improve the patient’s lung.

The EIT-τ images of this case highlights the clinical potential of τ to quickly identify bronchospasm at the bedside and adjust and monitor bronchodilator treatment and ventilator settings to prevent pulmonary hyperinflation, barotrauma, and atelectasis. Nonetheless, these EIT-τ images represent a single cross-sectional lung slice of 6 to 12 cm thickness only, which could potentially leave changes in regional ventilation occurring outside the monitored section undetected.

Although the EIT-based τ analyses of this case were performed retrospectively, these same calculations have now been implemented in the first clinical prototype such that EIT-τ images are now displayed in real time on a breath-by-breath basis. The method is currently under extensive clinical validation. Despite the current limitations, such novel EIT monitoring could improve perioperative patient management and safety in the near future.

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Name: Pedro de la Oliva, PhD, MD.

Contribution: This author helped design the study, collect and analyze the data, and write the manuscript.

Conflicts of Interest: Pedro de la Oliva declares no conflicts of interest.

Name: Andreas D. Waldmann, MSc.

Contribution: This author helped design the study, collect and analyze the data, and write the manuscript.

Conflicts of Interest: Andreas D. Waldmann is an employee and research support engineer of Swisstom AG.

Name: Stephan H. Böhm, MD.

Contribution: This author helped design the study, analyze the data, and write the manuscript.

Conflicts of Interest: Stephan H. Böhm is a cofounder, an employee, and a Chief Medical Officer of Swisstom AG; inventor of several EIT-related patents; and patent applications owned by Swisstom AG and Timpel SA.

Name: Cristina Verdú-Sánchez, MD.

Contribution: This author helped collect and analyze the data, and prepare the manuscript.

Conflicts of Interest: Cristina Verdú-Sánchez declares no conflicts of interest.

Name: Antonio Pérez-Ferrer, PhD, MD.

Contribution: This author helped collect and analyze the data, and prepare the manuscript.

Conflicts of Interest: Antonio Pérez-Ferrer declares no conflicts of interest.

Name: Elena Alvarez-Rojas, MD.

Contribution: This author helped design the study, collect and analyze the data, and prepare the manuscript.

Conflicts of Interest: Elena Alvarez-Rojas declares no conflicts of interest.

This manuscript was handled by: Raymond C. Roy, MD.

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