Neonates With Tracheomalacia Generate Auto-Positive End-Expiratory Pressure via Glottis Closure

Gunatilaka, C.C.; Hysinger, Erik B.; Schuh, Andreas; Gandhi, Deep; Higano, Nara S.; Xiao, Qiwei; Hahn, Andrew D.; Fain, Sean B.; Fleck, Robert; Woods, Jason C.; Bates, Alister J.

doi:10.1016/j.chest.2021.06.021

Cited by 7 publications

(2 citation statements)

References 48 publications

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“…Conversely, other applications may prioritize capturing dynamic anatomy in precise temporal positions with sharp boundaries to determine changes throughout the breath, such as tidal lung volume [35,36] or geometric analysis of central airway dynamics (e.g. tracheomalacia, obstructive sleep apnea) [37][38][39][40][41]; thus a linear weighting function with parameter choices τ = 2.5% and α = 3 may be considered since this provides a compromise between aSNR and motion suppression. For applications that require a middle-ground of structural images with temporal precision (e.g.…”

Section: Discussionmentioning

confidence: 99%

Comparison of weighting algorithms to mitigate respiratory motion in free-breathing neonatal pulmonary radial UTE-MRI

Gandhi,

Higano,

Hahn

et al. 2024

Biomed. Phys. Eng. Express

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Background: Thoracoabdominal MRI is limited by respiratory motion, especially in neonates who cannot perform breath-holds. To reduce motion blurring, radially-acquired MRI can be reconstructed from data acquired during specific respiratory phases (“hard-gating”), but this reduces image SNR. Various “soft-gating” reconstruction schemes have been proposed that incorporate data acquired outside the period of interest into reconstruction with diminished weighting. However, the choice of soft-gated weighting algorithm and parameters, and effect on image SNR and motion blurring, has not previously been explored. Methods: Purpose of this study is to map how variable data inclusion and weighting affect SNR and motion blurring in respiratory-gated reconstructions of neonatal radial lung MRI, using existing and novel soft-gated weighting functions. Ten neonatal subjects with respiratory abnormalities from the neonatal intensive care unit were imaged using a 1.5T neonatal-sized scanner and 3D radial ultrashort echo-time (UTE) sequence. The apparent SNR and motion blurring of retrospectively respiratory-gated UTE-MRI were compared between images reconstructed using ungated, hard-gated, and several soft-gating weighting algorithms and parameters (using exponential, sigmoid, inverse, and linear weighting decay outside the period of interest). Motion blurring was measured by the maximum derivative of image intensity at the diaphragm (MDD). Results: Soft-gating functions produce higher aSNR than hard-gated images using equivalent numbers of projections (%Nproj), but with lower MDD. While aSNR was approximately linear with %Nproj for each algorithm, MDD performance diverged between functions as %Nproj decreased. Algorithm performance was relatively consistent between subjects, except in images with high noise, where function performance differed.Conclusion: The temporal pattern of undersampling has a significant effect on image quality; for the same %Nproj, a wider temporal distribution of included data produces higher aSNR, a narrower temporal distribution increases MDD. Therefore, timing strategy of undersampling schemes can be optimized depending on the required application’s compromise between aSNR and MDD.

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Section: Discussionmentioning

confidence: 99%

Comparison of weighting algorithms to mitigate respiratory motion in free-breathing neonatal pulmonary radial UTE-MRI

Gandhi,

Higano,

Hahn

et al. 2024

Biomed. Phys. Eng. Express

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“…Another possible reason is the impact of sedation on glottic motion. Children with TM are able generate auto‐positive end expiratory pressure PEEP) with glottic closure to presumably raise lung volume and increase expiratory flow 15,31 . During sedation, there is clearly decrease in muscle tone of the upper airway, so the ability to generate auto‐PEEP is lost which could result in different magnitude of tracheal alteration compared to fully awake state.…”

Section: Discussionmentioning

confidence: 99%

Pulmonary function of children with tracheomalacia and associated clinical factors

Boonjindasup

Marchant

McElrea

et al. 2022

Pediatric Pulmonology

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Objectives Spirometry is easily accessible yet there is limited data in children with tracheomalacia. Availability of such data may inform clinical practice. We aimed to describe spirometry indices of children with tracheomalacia, including Empey index and flow‐volume curve pattern, and determine whether these indices relate with bronchoscopic features. Methods From the database of children with tracheomalacia diagnosed during 2016–2019, we reviewed their flexible bronchoscopy and spirometry data in a blinded manner. We specially evaluated several spirometry indices and tracheomalacia features (cross‐sectional lumen reduction, malacic length, and presence of bronchomalacia) and determined their association using multivariable regression. Results Of 53 children with tracheomalacia, the mean (SD) peak expiratory flow (PEF) was below the normal range [68.9 percent of predicted value (23.08)]. However, all other spirometry parameters were within normal range [Z‐score forced expired volume in 1 s (FEV1) = −1.18 (1.39), forced vital capacity (FVC) = −0.61 (1.46), forced expiratory flow between 25% and 75% of vital capacity (FEF25%–75%) = −1.43 (1.10), FEV1/FVC = −1.04 (1.08)], Empey Index = 8.21 (1.59). The most common flow‐volume curve pattern was the “knee” pattern (n = 39, 73.6%). Multivariable linear regression identified the presence of bronchomalacia was significantly associated with lower flows: FEV1 [coefficient (95% CI) −0.78 (−1.54, −0.02)], FEF25%–75% [−0.61 (−1.22, 0)], and PEF [−12.69 (−21.13, −4.25)], all p ≤ 0.05. Other bronchoscopic‐defined tracheomalacia features examined (cross‐sectional lumen reduction, malacic length) were not significantly associated with spirometry indices. Conclusion The “knee” pattern in spirometry flow‐volume curve is common in children with tracheomalacia but other indices, including Empey index, cannot be used to characterize tracheomalacia. Spirometry indices were not significantly associated with bronchoscopic tracheomalacia features but children with tracheobronchomalacia have significantly lower flow than those with tracheomalacia alone.

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Diagnostic Approach to Tracheomalacia and Medical Management

Hysinger,

Zak

2024

Pediatric Aerodigestive Medicine

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Neonates With Tracheomalacia Generate Auto-Positive End-Expiratory Pressure via Glottis Closure

Cited by 7 publications

References 48 publications

Comparison of weighting algorithms to mitigate respiratory motion in free-breathing neonatal pulmonary radial UTE-MRI

Comparison of weighting algorithms to mitigate respiratory motion in free-breathing neonatal pulmonary radial UTE-MRI

Pulmonary function of children with tracheomalacia and associated clinical factors

Diagnostic Approach to Tracheomalacia and Medical Management

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