Heterogeneous Changes in Lung Structure and Mechanics in Two-Hit Lung Injury Models

Bilodeaux, J.; Osovskaya, M.; Wallbank, Alison; Farooqi, H.; Smith, Burton

doi:10.1164/ajrccm-conference.2022.205.1_meetingabstracts.a5323

Cited by 1 publication

(3 citation statements)

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“…Comparison to manual classification (Figure 1) shows that the sensitivity for 'injury' pixels was 0.78, indicating that automated segmentation and the morphological post-processing steps accurately describes 'injury' pixels, while the specificity of 0.85 indicates that most non-injury pixels are correctly excluded. In a prior study a different observer (BJS) performed manual morphometry (stereology) on the same samples (Bilodeaux et al, 2023) and found that the percentage of collapsed septal tissue in the entire lung was 14.55% for LAV and 2.28% for CTRL. In the current study the automated approach yielded 19.82% in the LAV group and 9.88% in the CTRL group.…”

Section: Discussionmentioning

confidence: 99%

“…The current study is a secondary analysis of images generated in previously reported experiments (Bilodeaux et al, 2023) and the key experimental details are summarized below. The study was conducted on female C57/BL6 mice, aged seven to 10 weeks, and was approved by the University of Colorado Denver Institutional Animal Care and Use Committee (IACUC) under protocol #00230.…”

Section: Animal Proceduresmentioning

confidence: 99%

“…The control group received 6 minutes of stabilizing low tidal volume ventilation at PEEP = 3 cmH 2 O. All groups then received a series of lung function measurements with PEEPs ranging from 0 to 15 cmH 2 O as detailed elsewhere (Bilodeaux et al, 2023). Total ventilation time was ≈35 min for CTRL and ≈60 min for LAV.…”

Section: Animal Proceduresmentioning

confidence: 99%

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A scale-free model of acute and ventilator-induced lung injury: a network theory approach inspired by seismology

Gottman,

Smith

2024

Front. Netw. Physiol.

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IntroductionAcute respiratory distress syndrome (ARDS) presents a significant clinical challenge, with ventilator-induced lung injury (VILI) being a critical complication arising from life-saving mechanical ventilation. Understanding the spatial and temporal dynamics of VILI can inform therapeutic strategies to mitigate lung damage and improve outcomes.MethodsHistological sections from initially healthy mice and pulmonary lavage-injured mice subjected to a second hit of VILI were segmented with Ilastik to define regions of lung injury. A scale-free network approach was applied to assess the correlation between injury regions, with regions of injury represented as ‘nodes’ in the network and ‘edges’ quantifying the degree of correlation between nodes. A simulated time series analysis was conducted to emulate the temporal sequence of injury events.ResultsAutomated segmentation identified different lung regions in good agreement with manual scoring, achieving a sensitivity of 78% and a specificity of 85% across ‘injury’ pixels. Overall accuracy across ‘injury’, ‘air’, and ‘other’ pixels was 81%. The size of injured regions followed a power-law distribution, suggesting a ‘rich-get-richer’ phenomenon in the distribution of lung injury. Network analysis revealed a scale-free distribution of injury correlations, highlighting hubs of injury that could serve as focal points for therapeutic intervention. Simulated time series analysis further supported the concept of secondary injury events following an initial insult, with patterns resembling those observed in seismological studies of aftershocks.ConclusionThe size distribution of injured regions underscores the spatially heterogeneous nature of acute and ventilator-induced lung injury. The application of network theory demonstrates the emergence of injury ‘hubs’ that are consistent with a ‘rich-get-richer’ dynamic. Simulated time series analysis demonstrates that the progression of injury events in the lung could follow spatiotemporal patterns similar to the progression of aftershocks in seismology, providing new insights into the mechanisms of injury distribution and propagation. Both phenomena suggest a potential for interventions targeting these injury ‘hubs’ to reduce the impact of VILI in ARDS management.

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Section: Discussionmentioning

confidence: 99%

Section: Animal Proceduresmentioning

confidence: 99%