Development and evaluation of a decompression stress index based on tissue bubble dynamics.

Format:

Book

Thesis/Dissertation

Author/Creator:

Gernhardt, Michael Landon.

Contributor:

Scherer, Peter, advisor.

Lambertsen, C. J. (Christian James), 1917-2011, advisor.

University of Pennsylvania.

Language:

English

Subjects (All):

Medical physics.

Kinesiology.

0575.

0760.

Penn dissertations--Bioengineering.

Bioengineering--Penn dissertations.

Local Subjects:

Penn dissertations--Bioengineering.

Bioengineering--Penn dissertations.

0575.

0760.

Physical Description:

327 pages

Contained In:

Dissertation Abstracts International 52-11B.

System Details:

Mode of access: World Wide Web.

text file

Summary:

Conventional decompression models use tissue inert gas supersaturation as a index of decompression stress. These models assume that controlling tissue supersaturation to within tolerable levels will prevent the occurrence of decompression sickness (DCS). These models have consistently been ineffective at preventing DCS for deep and prolonged exposures. These limitations compromise the safety and effectiveness of diving operations.

It is widely accepted that the symptoms of DCS are initiated by the separation and expansion of gas phase. It was hypothesized that a decompression stress index based on tissue bubble growth dynamics should predict the occurrence of DCS symptoms better than conventional stress indices based on tissue supersaturation.

To test this hypothesis, a mathematical model of tissue bubble dynamics was developed and evaluated. The predictions of the bubble growth and supersaturation indices were compared to observations of DCS (430 cases) in laboratory trials (6,457 exposures) using the Logistic Regression Method.

Qualitative observations of DCS were also predicted with the bubble dynamics model and compared to the predictions of the supersaturation index.

The results of the statistical analysis showed that the bubble growth index consistently provided a better (statistically significant (p $<0$.05)) prediction (than supersaturation or exposure phase index) and fit of the laboratory DCS incidence data. The results of the qualitative analysis showed that the bubble growth index predicted: (1) A pattern of increasing decompression stress with increasing exposure phase severity, that was consistent with the results of 100,000 decompression records. (2) Patterns of DCS latency times that were consistent with observed average latency times. (3) Consistent levels of decompression stress across a range of empirically defined no decompression limits. The predictions of the supersaturation index were not consistent with these qualitative DCS observations.

The results demonstrate that the tissue bubble dynamics model is a better predictor of decompression stress and DCS symptoms than supersaturation. The results also suggest that the levels of tolerable supersaturation in conventional decompression models do not prevent the formation and expansion of gas phase. Gas phase growth, although initiated by supersaturation, is also a function of: (1) The time course of tissue supersaturation. (2) The diffusion of gases through the dissolved/free gas phase diffusion barrier. (3) Gas phase pressure/volume response to ambient pressure changes. (4) Tissue elastic response to gas phase growth.

Notes:

Thesis (Ph.D. in Bioengineering) -- Graduate School of Arts and Sciences, University of Pennsylvania, 1991.

Source: Dissertation Abstracts International, Volume: 52-11, Section: B, page: 5712.

Advisers: C. J. Lambertsen; Peter Scherer.

Local Notes:

School code: 0175.

Access Restriction:

Restricted for use by site license.