ABSTRACT
Background
Central Apnoea of prematurity (AoP) is a common complication in preterm infants. AoP impact oxygenation but it is unclear what its effect is on lung volume and ventilation distribution. Electrical Impedance Tomography is a technique able to continuously and bedside monitor lung volume changes in preterm infants.
Methods
In a subset of preterm infants of the CRADL project (Continuous Regional Analysis device for neonate Lung) we extracted, using a self‐developed automatic detection algorithm and followed by a hand check central AoP, EIT tracings. These EIT tracings were analysed pre‐, during and post apnoea for changes in relative end expiratory lung impedance (EELI), tidal volume, breathing rate, minute volume and ventilation distribution.
Results
In 15 preterm infants, 203 apnoeas were identified and included into this study. During apnoeas a significant drop (p < 0.05) in relative EELI was seen but this restored to pre‐apnoea levels, mediated by an increased median tidal volume (0.43 AU [0.34–0.57] to 0.57 AU [0.47–0.70], p < 0.05). Ventilation distribution on a regional level (right—left, anterior—posterior or centre of ventilation) showed no changes pre‐ and post‐ apnoea.
Conclusion
Central AoP results in a significant decrease in EELI but this restores to pre‐apnoea levels by compensatory increased tidal volume. No changes in ventilation distribution were detected after an apnoea.
Keywords: apnoea of Prematurity, electrical impedance tomography, nCPAP, newborn, preterm infant
1. Introduction
Apnoea of prematurity (AOP) is a common complication of preterm birth and has widely been defined as cessation of breathing that lasts for more than 15 s, usually accompanied by desaturation or bradycardia [1, 2, 3]. In preterm infants 10%–25% of all described AOP are of central origin and if coincides with a hypoxic event is associated with an increased risk for long term adverse neurodevelopmental outcome [4, 5, 6]. It is however unknown if the disturbance in oxygenation and gas exchange during AOP is only caused by disruption in breathing or that changes in (regional) lung aeration also contributes to this process. In addition, it is unknown if all alterations in lung aeration completely recover to normal conditions when the central apnoea resolves.
Important factors for this lack in knowledge is the absent of adequate bedside, continuous‐ and regional monitoring of lung aeration and ventilation in preterm infants. In daily practise monitoring and classification of AOP are based on chest impedance, using standardized ECG electrodes. In literature respiratory inductive has been used as an alternative monitoring tool but only generated information on general absence or presence of breathing and don't inform users on the impact of AOP on end expiratory lung volume (EELV) or especially regional ventilation changes [7, 8, 9]. Recently, Gaertner et al showed in a 2 h cross over study of nasal continuous airway pressure (nCPAP) and nasal high frequency ventilation in a cohort of 30 preterm infants using Electrical Impedance Tomography (EIT) that during apnoeas a drop in end expiratory lung impedance (EELI) was detected which returned to before conditions after spontaneous breathing recovered [10]. This was due to an increase in tidal volume in the first five breaths after apnoeas.
EIT has shown to accurately measure at the bedside and radiation free, regional impedance changes in a cross‐section of the thorax in preterm infants [11, 12]. These regional impedance changes are highly correlated to actual EELV and ventilation changes making EIT extremely suitable to analyse the impact of AOP of central type on aeration and ventilation [13, 14, 15]. We used a subgroup of the Continuous Regional Analysis device for neonate Lung (CRADL) (NCT02962505) data set to identify AOP of central origin and evaluate its effect on regional aeration and ventilation using pre‐ and post AOP data.
2. Materials and Methods
The CRADL project (EU grant No. 668259) was a multicentre 72 h observational EIT study including 200 infants and was carried out from November 2016 until March 2019. Patients were eligible if they were admitted to the neonatal or pediatric intensive care unit with respiratory failure needing any form of respiratory support. Exclusion criteria were a body weight < 600 g, post menstrual age < 25 weeks or those infants suffering from thorax skin lesions making it impossible to place the EIT belt around the thorax. A subset of 15 preterm infants with frequent AOP, all included at the Amsterdam UMC, were selected for analysis. The study was approved by the medical ethics committee of the Amsterdam UMC (METC 2016/184) and written parental informed consent was obtained before EIT recordings started.
EIT recordings were acquired at a scan rate of 48 scans/s using the SenTec BB2 system (SenTec, AG, Switzerland) and a neonatal nonadhesive textile 32‐electrode belt which was placed around the preterm infants chest circumference between the 5th and 6th intercostal space. Neonatal ultrasound gel (Aquasonic 100, Parker Laboratory, USA) was used to improve belt to skin conductance. Clinicians were blinded for the recordings and daily care was performed as usual without study interventions.
For apnoea analysis first off line image reconstruction was performed using the Graz consensus Reconstruction algorithm for EIT [16]. Next, a custom made apnoea detection algorithm was used to detect a stop in breathing for more than 15 s throughout the 72 h of recording. The automated selected periods were than hand checked by MM for clear recording, accurate detection, and apnoea's of central origin. Events showing motion related artifacts, asynchronous regional impedance deflection or belt instability were excluded as obstructive/mixed or uncertain. Only high‐confidence central events showing no tidal breathing, without movement artifacts or paradoxical regional impedance activity were included. Representative tracings of in‐ and excluded patterns are shown in Supporting Information S1: Figure 1.
Per included apnoea pre‐, during‐ and post apnoea periods were selected (Figure 1). Pre and post periods were defined as 20 s of tidal breathing before and after the apnoea respectively. If no 20 s period could be identified a period with a minimum of 10 breaths was used. Using a neonatal optimized breath detection algorithm, time points of end‐inspiration and end‐expiration were detected and used for calculation of impedance based relative tidal volume (Vt), breathing rate (BR) and minute volume (MV) [17]. To evaluate the change in relative end expiratory lung impedance (EELI), the impedance levels at end‐expiration pre‐ and post‐apnoea were used and compared to the deepest point in impedance during the apnoea (Figure 1). This analysis was also performed on a regional level for the anterior, posterior, right and left halve of the thorax.
Figure 1.
Representative change in impedance during an apnoea of prematurity, start indicated by the dotted line, in a preterm infant on nasal continuous airway pressure with pre‐ and post‐apnoea selected time frames including stable tidal ventilation. The deepest point (DP) in drop of impedance during the apnoea is indicated by the arrow.
Next, functional EIT images were reconstructed for the pre‐ and post‐apnoea period and used for determination of ventilation distribution in the anterior‐ and posterior halve and right‐ and left halve of the EIT cross section. Also the centre of ventilation in the anterior—posterior‐ and right—left axis were calculated. In addition to assess the ventilation distribution change pre‐ and post‐apnoea the f‐EIT images were divided in 10% slices in the anterior– posterior axis. To summarize data the entire cross section was set at 100% and for each slice the ventilation distribution calculated and plotted following previous described analysis [18, 19].
Statistical analysis were performed using GraphPad Prism 8.2.1 (GraphPad Software, San Diego, California). Depending on their distribution, data were expressed as mean with standard deviation or median with interquartile ranges. Comparative analyses were performed using One‐Way‐ANOVA‐ and Kruskal–Wallis for multiple comparisons. A p‐value of < 0.05 was considered statistically significant.
3. Results
Table 1 shows the baseline characteristics and respiratory support of the 15 included preterm infants. A total of 1121 apnoea's were identified by the custom made apnoea detection algorithm. After hand checking 203 tracings were used for final analysis as most tracings were disturbed or wrongly detected an apnoea. The most common reasons were that too many electrodes had insufficient skin connection, the EIT tracing was disturbed by movement artifacts or the apnoea was an obstructive or mixed type. The posture of the infant during the recordings were in supine position or mildly turned on the side.
Table 1.
Patient characteristics.
| Characteristic | Value (n = 15) |
|---|---|
| Gestational age at birth (weeks) | 27.2 [25.6–27.6] |
| Postmenstrual age at measurement (weeks) | 31.3 [28.8–32.7] |
| Weight at measurement (g) | 1290 [1078–1630] |
| Diagnosis (n (%)) | |
|
14 (93) |
|
1 (7) |
| Mode of respiratory support (n (%)) | |
|
2 (13) |
|
9 (60) |
|
4 (27) |
| Level of respiratory support | |
|
6 [6–7.5] |
|
19 [18.5–19.5] |
|
55 [52.5–57.5] |
|
6.5 [5–7.3] |
| FiO2 | 0.26 [0.21–0.31] |
| Duration of recording (hrs) | 71 [48–72] |
| Apnoea's included per patient (n) | 10 [5–21] |
Note: Data are presented as n or median [IQR].
Abbreviations: HFNC, high flow nasal cannula; nCPAP, nasal continuous positive airway pressure; NIPPV, noninvasive positive pressure ventilation; PEEP, positive end‐expiratory pressure; PIP, positive inspiratory pressure.
Relative EELI dropped significantly (p < 0.05) during an apnoea to a median of 25.3 AU [21.1–27.7] but restored to pre apnoea (26.9 AU [24.0–28.8]) levels post apnoea (26.7 AU [24.2–28.9]) (Figure 2). Relative tidal volume increased significantly (p < 0.05) from a median of 0.43 AU [0.34–0.57] to 0.57 AU [0.47–0.70] post apnoea resulting in a significant higher minute volume post apnoea as the frequency was unchanged (Figure 3). This significant increase corresponds with 32% in relative VT pre‐apnoea. This effect was also seen on a regional level pre, during and post apnoea but with no significant change between regions Ventilation distribution of tidal volume was unaffected by the apnoea as no significant change (One‐Way ANOVA) was seen in the anterior/posterior halve, right/left halve or in the anterior to posterior axis when comparing pre to post apnoea conditions (Table 2 and Figure 4).
Figure 2.
Changes in end expiratory lung impedance (EELI) pre (white boxes), during (dark grey boxes) and post (light grey boxes) AOP of central origin in the entire cross section (A) and in the regional halves (right and left halve and anterior and posterior (B)). Data are presented as median with interquartile ranges. *p < 0.05 (Kruska–Wallis test).
Figure 3.
Changes in tidal volume (Vt), breathing rate (BR) and minute volume (MV), pre (white boxes) and post (light grey boxes) AOP of central origin. Data are presented as median with interquartile ranges. *p < 0.05 (Kruska–Wallis test).
Table 2.
Functional EIT based ventilation distribution characteristics pre and post AoP.
| Ventilation distribution characteristics | Pre (n = 15) | Post (n = 15) |
|---|---|---|
| Anterior half (%) | 44.5 ± 9.9 | 44.7 ± 9.4 |
| Posterior half (%) | 55.5 ± 9.9 | 55.3 ± 9.4 |
| Right half (%) | 53.0 ± 10.7 | 53.0 ± 10.5 |
| Left half (%) | 47.0 ± 10.7 | 47.0 ± 10.5 |
| Center of ventilation, A‐P axis (%) | 52.6 ± 2.4 | 52.6 ± 2.3 |
| Center of ventilation, R‐L axis (%) | 50.7 ± 3.0 | 50.7 ± 3.0 |
| GI index | 1.6 ± 0.8 | 1.6 ± 0.6 |
Note: A = anterior, L = left, P = posterior, R = right. Data are presented as mean ± SD.
Figure 4.
Functional EIT based regional ventilation distribution of spontaneous breaths in 10% slices in the anterior–posterior axis. Panel A shows pre apnoea conditions and Panel B post apnoea.
4. Discussion
Premature infants develop a degree of periods of cessation in spontaneous breathing due to immature brainstem coordination and is called Apnoea Of Prematurity. Long term studies have shown an association between AOP and a poor neurological outcome [4]. In this study we found similar findings in pre‐ and post‐apnoea lung volume distribution and EELI as reported by Gaertner et al. in a short crossover trial of nCPAP and nasal high frequency ventilation in a cohort of similar aged preterm infants [10]. Therefore confirming the true effect of AOP of central origin and its impact on lung volume but also underlining the strong and reliable capability of EIT in the preterm population.
In this study we selected a small cohort from the CRADL project, an 72 h EIT observational study including 200 subjects needing any form of respiratory support, and although not the primary end point we were able to gather continuous EIT data pre‐, during and post AOP. We selected patients based on the retrospective knowledge infants having apnoea's of mostly central origin during the recording time and we only selected apnoea's for analysis if the recording was clear with no artifacts of any origin.
We found that AOP resulted in a median drop in relative EELI 3.7 times tidal volume but EELI restored to similar levels in relation to pre AOP conditions. There were no difference post apnoea in relative EELI on a regional nondependent vs. dependent lung regions. During apnoea, there appears to be a uniform loss of EELI across lung regions, which is restored evenly within the first 20 s post‐apnoea. We speculate that this uniform loss is due to the combined influence of positioning of the infant and continuous nCPAP, preventing preferential loss and recruitment of specific lung regions. The preterm infants used larger tidal volumes, resulting in higher minute volume, to restore and maintain these relative EELI levels post AOP but this didn't affected ventilation or aeration distribution regionally. This suggests that preterm infants have a higher work of breathing post AOP to compensate and bring back EELI to normal functional residual capacity levels and if AOP reoccurs frequently one can image leads to fatigue and if compensating fails lead to progressive respiratory failure needing more respiratory support. The transient fall in EELI during the apnoea likely reflects passive lung deflation due to diminished diaphragmatic tone and an open glottis allowing recoil of the respiratory system to lower lung volume. The subsequent compensatory rise in relative Vt (~ 32% above pre‐apnoea) suggests active recruitment to restore functional residual capacity.
Not surprising, EIT was able to monitor and show AOP very clearly as seen in Figure 1 and therefore EIT is suitable for detecting AOP in preterm infants. However, it must be determined how reliable EIT will be in future research as this study only focused on analysing the impact on tidal volume and EELI and not EIT as an apnoea detection monitor. Especially, as we excluded many tracings due to movement artifacts and other tools like diaphragmatic EMG (dEMG) seem to be more reliable in detecting and classifying AOP [20]. Continuous neonatal EIT may complement conventional chest impedance and dEMG by providing regional aeration trends, detecting volume loss, and quantifying post‐apnoea effort. Combined EIT and dEMG could improve apnoea phenotyping and guide noninvasive support. In our analysis, 20% of events were purely central AOP, while the rest included obstructive/mixed types, poor‐quality signals, or movement artefacts, highlighting the challenges of reliable long‐term EIT monitoring in preterm infants.
This study has some limitations that need to be addressed. First, we only included AOP of central origin as this was the most frequent and reliable apnoea which could be distilled form the EIT data without vital parameters like heart rate and saturation data available. We believe however that the impact of pathophysiological effects will not be any different in AOP of obstructive or mixed type but future research should focus on simultaneous recording of EIT and vital parameters during AOP. Secondly, as part of the definition of AOP is besides a stop in breathing a coinciding bradycardia or desaturation and in the CRADL project unfortunately only continuously EIT data was recorded and no heart rate or saturation. Nevertheless, as chest impedance changes are the golden standard for cardiorespiratory monitoring in preterm infants we believe that the selected periods are valid for AOP of central origin. Thirdly, we only focused on the short term effect of AOP and it is unknown if the found compensation mechanisms will go back to normal in the minutes after AOP. Fourthly, we didn't apply a band pass filter in the breathing frequency domain, as would have removed the relative EELI changes. As a result, cardiac‐related impedance changes were also not filtered and may have influenced the results. However, since the data are presented as median or mean changes, and cardiac related impedance variations are relatively small, the overall impact is expected to be minimal. We used the EIT signal to differentiate between central and obstructive apnoea. However, the accuracy of EIT to classify apnoea has limitations compared with other modalities such polysomnography and transcutaneous EMG. We can therefore state with absolute certainty that all events were central of origin. Finally, most of the included preterm infants were relatively stable with a median of 10 apnoea's per 71 h median time of recording and results could have been different in infant with more apnoea's per time unit. However, the question is if the pathophysiological processes would be any different.
AOP from central type results in a drop of EELI which restores to normal values post apnoea using where preterm infants use a larger tidal volume and minute volume to compensate this loss. It seems that AOP doesn't affect regional ventilation distribution or aeration. Future research should evaluate whether integrating EIT into routine monitoring enables earlier detection of clinically significant volume loss, guide individualized PEEP adjustments and reduces recurrent apnoea in preterm infants.
STROBE Statement
The manuscript has been written following the STROBE guidelines and the checklist has been uploaded as Supporting Material for review.
Author Contributions
Martijn Miedema: conceptualization, investigation, methodology, writing – review and editing, writing – original draft, software, formal analysis, validation, visualization, data curation. Rebecca Yerworth: methodology, writing – review and editing, formal analysis, software, validation. Andreas D. Waldmann: methodology, formal analysis, writing – review and editing, validation. Inéz Frerichs: supervision, writing – review and editing, project administration. Richard Bayford: supervision, writing – review and editing, funding acquisition, project administration, resources. Anton H. Van Kaam: supervision, writing – original draft, writing – review and editing, methodology, conceptualization.
Ethics Statement
The study was approved by the medical ethics committee of Amsterdam UMC (METC 2016/184), and written informed consent was obtained from parents before the initiation of EIT recordings. Parental consent was requested by the contributing researchers of the CRADL project, with parents given a minimum of 24 h to consider their decision. After receiving positive consent, EIT recordings commenced. Source of financial support. European Union's Horizon 2020 Research and Innovation Programme. Clinicaltrials.gov identifier NCT02962505.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Figure S1. Panel A and B show examples of apnoea of prematurity included for analysis. Panel C and D show examples of excluded tracings.
Miedema M., Yerworth R., Waldmann A. D., Frerichs I., Bayford R., and Van Kaam A. H., “Changes in Lung Volume and Ventilation During Apnoea of Prematurity Using EIT,” Pediatric Pulmonology 0 (2025), 10.1002/ppul.71369.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1. Panel A and B show examples of apnoea of prematurity included for analysis. Panel C and D show examples of excluded tracings.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.