Ultrasonographic modeling of diaphragm function: A novel approach to respiratory assessment

Danielle N O'Hara, Andrey Pavlov, Erin Taub, Sahar Ahmad, Danielle N O'Hara, Andrey Pavlov, Erin Taub, Sahar Ahmad

Abstract

Objectives: Bedside ultrasound techniques have the unique ability to produce instantaneous, dynamic images, and have demonstrated widespread utility in both emergency and critical care settings. The aim of this article is to introduce a novel application of this imaging modality by utilizing an ultrasound based mathematical model to assess respiratory function. With validation, the proposed models have the potential to predict pulmonary function in patients who cannot adequately participate in standard spirometric techniques (inability to form tight seal with mouthpiece, etc.).

Methods: Ultrasound was used to measure diaphragm thickness (Tdi) in a small population of healthy, adult males at various points of the respiratory cycle. Each measurement corresponded to a generated negative inspiratory force (NIF), determined by a handheld meter. The data was analyzed using mixed models to produce two representative mathematical models.

Results: Two mathematical models represented the relationship between Tdi and NIFmax, or maximum inspiratory pressure (MIP), both of which were statistically significant with p-values <0.005: 1. log(NIF) = -1.32+4.02×log(Tdi); and 2. NIF = -8.19+(2.55 × Tdi)+(1.79×(Tdi2)).

Conclusions: With validation, these models intend to provide a method of estimating MIP, by way of diaphragm ultrasound measurements, thereby allowing evaluation of respiratory function in patients who may be unable to reliably participate in standard spirometric tests.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. Scatter plot and fitted line…
Fig 1. Scatter plot and fitted line of the linear regression model with logarithmic transformation of NIF versus the absolute diaphragm thickness (Tdi).
The best-fit line is represented by y = -1.32 + 4.02× log(x). This mixed model using logarithmic transformation of x and y variables demonstrated a p-value <0.0001.
Fig 2. Scatter plot and fitted line…
Fig 2. Scatter plot and fitted line of the general linear model used to represent the quadratic relationship between NIF and Tdi.
The best-fit line is represented by y = -8.19 + (2.55 × Tdi) + (1.79 × (Tdi2)). This mixed model of the original untransformed data demonstrated a p-value <0.005.

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