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Dynamic relative regional lung strain estimated by computed tomography and electrical impedance tomography in ARDS patients

BACKGROUND: In the acute distress respiratory syndrome (ARDS), specific lung regions can be exposed to excessive strain due to heterogeneous disease, gravity-dependent lung collapse and injurious mechanical ventilation. Computed tomography (CT) is the gold standard for regional strain assessment. An...

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Detalles Bibliográficos
Autores principales: Brito, Roberto, Morais, Caio C. A., Lazo, Marioli T., Guiñez, Dannette V., Gajardo, Abraham I. J., Arellano, Daniel H., Amato, Marcelo B. P., Cornejo, Rodrigo A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668403/
https://www.ncbi.nlm.nih.gov/pubmed/38001485
http://dx.doi.org/10.1186/s13054-023-04748-4
Descripción
Sumario:BACKGROUND: In the acute distress respiratory syndrome (ARDS), specific lung regions can be exposed to excessive strain due to heterogeneous disease, gravity-dependent lung collapse and injurious mechanical ventilation. Computed tomography (CT) is the gold standard for regional strain assessment. An alternative tool could be the electrical impedance tomography (EIT). We aimed to determine whether EIT-based methods can predict the dynamic relative regional strain (DRRS) between two levels of end-expiratory pressure (PEEP) in gravity-non-dependent and dependent lung regions. METHODS: Fourteen ARDS patients underwent CT and EIT acquisitions (at end-inspiratory and end-expiratory) at two levels of PEEP: a low-PEEP based on ARDS-net strategy and a high-PEEP titrated according to EIT. Three EIT-based methods for DRRS were compared to relative CT-based strain: (1) the change of the ratio between EIT ventilation and end-expiratory lung impedance in arbitrary units ([ΔZ(AU low-PEEP)/EELI(AU low-PEEP)]/[ΔZ(AU high-PEEP)/EELI(AU high-PEEP)]), (2) the change of ΔZ/EELI ratio calibrated to mL ([ΔZ(ml low-PEEP)/EELI(ml low-PEEP)]/[ΔZ(ml high-PEEP)/EELI(ml high-PEEP)]) using CT data, and (3) the relative change of ∆Z(AU) (∆Z(AU low-PEEP)/∆Z(AU high-PEEP)). We performed linear regressions analysis and calculated bias and limits of agreement to assess the performance of DRRS by EIT in comparison with CT. RESULTS: The DRRS assessed by (ΔZ(ml low-PEEP)/EELI(ml low-PEEP))/(ΔZ(ml high-PEEP)/EELI(ml high-PEEP)) and ∆Z(AU low-PEEP)/∆Z(AU high-PEEP) showed good relationship and agreement with the CT method (R(2) of 0.9050 and 0.8679, respectively, in non-dependent region; R(2) of 0.8373 and 0.6588, respectively, in dependent region; biases ranging from − 0.11 to 0.51 and limits of agreement ranging from − 0.73 to 1.16 for both methods and lung regions). Conversely, DRRS based on EELI(AU) ([ΔZ(AU low-PEEP)/EELI(AU low-PEEP)]/[ΔZ(AU high-PEEP)/EELI(AU high-PEEP)]) exhibited a weak negative relationship and poor agreement with the CT method for both non-dependent and dependent regions (R(2) ~ 0.3; bias of 3.11 and 2.08, and limits of agreement of − 2.13 to 8.34 and from − 1.49 to 5.64, respectively). CONCLUSION: Changes in DRRS during a PEEP trial in ARDS patients could be monitored using EIT, based on changes in ΔZ(mL)/EELI(ml) and ∆Z(AU). The relative change ∆Z(AU) offers the advantage of not requiring CT data for calibration.