Download PDF
Methods Inf Med 2012; 51(01): 21-28
DOI: 10.3414/ME11-01-0017
Original Articles
Schattauer GmbH

Modelling of Diffusing Capacity Measurement Results in Lung Microangiopathy Patients

A Novel Pulmonary Diagnostic Support
R. Kalicka
1   Department of Biomedical Engineering, Gdansk University of Technology, Gdansk, Poland
,
W. Słomiński
1   Department of Biomedical Engineering, Gdansk University of Technology, Gdansk, Poland
,
K. Kuziemski
2   Department of Allergology, Medical University of Gdansk, Gdansk, Poland
› Author Affiliations
Further Information

Publication History

received:21 February 2011

accepted:12 August 2011

Publication Date:
20 January 2018 (online)

    Permissions and Reprints

Summary

Background: Lung microangiopathy is a little known negative influence of diabetes mellitus on the functioning of the lungs. In current medical practice lung microangiopathy is diagnosed by comparing two measurements of lung diffusing capacity – once with the subject standing and once with the subject lying down. The necessity to take two measurements is inconvenient.

Objectives: The aim of this study is to design a supportive method for diagnosing lung microangiopathy. This will be based on routinely performed pulmonary measurements as well as on investigation of process modelling and data processing.

Methods: A model of the diffusion of oxygen from the alveoli to the blood has been described with a set of differential equations. The idea of the proposed model is based on the physiological analysis of the oxygen flow (caused by a concentration gradient) and on general knowledge regarding the kinetics of associating oxygen with haemoglobin. The model parameters are estimated using diffusing capacity and alveolar volume measurements – routinely performed in pulmonary tests.

Results: The model parameter estimates proved good candidates for the binary classification of the presence or absence of micro-angiopathy. The proposed classification procedure, based on parameter values and established diagnostic thresholds, gives sensitivity Sens = 79.34% and specificity Spec = 87.08%. The results of classification with the use of diffusing capacity measurement are worse: Sens = 62.12% and Spec = 79.89%.

Conclusions: The proposed classification procedure is based on the model parameters. These have proved to be sensitive indicators of lung microangiopathy. Close to 80% of micro-angiopathy cases have been classified as such. Less than 20% were false alarms. The oxygen pathway model allows for simulations. Blood saturation and oxygen partial pressure have been simulated for the organism’s various needs for oxygen, both for the normal and the impaired alveoli-capillary barrier.

Keywords

Models - decision support - lung - diffusion
 

  • References

  • 1 Dalquen P. The lung in diabetes mellitus. Respiration 1999; 66: 12-13.
    CrossrefPubMedGoogle Scholar
  • 2 Kida K, Utsuyama M, Takizawa T, Thurlbeck WM. Changes in lung morphologic features and elasticity caused by streptozotocin-induced diabetes mellitus in growing rats. Am Rev Respir Dis 1983; 128: 125-131.
    CrossrefPubMedGoogle Scholar
  • 3 Popov D, Simionescu M. Alterations of lung structure in experimental diabetes, and diabetes associated with hyperlipidaemia in hamsters. Eur Respir J. 1997; 10: 1850-1858.
    CrossrefPubMedGoogle Scholar
  • 4 Kodolova IM, Lysenko LV, Saltykov BB. Changes in the lungs in diabetes mellitus. Arkh Patol 1982; 44: 35-75.
    PubMedGoogle Scholar
  • 5 Matsubara T, Hara F. The pulmonary function and histological studies of the lung in diabetes mellitus. Journal of Nippon Medical School 1991; 58: 528-536.
    CrossrefPubMedGoogle Scholar
  • 6 Weynand B, Jonckheere A, Frans A, Rahier J. Diabetes mellitus induces a thickening of the pulmonary basal lamina. Respiration 1999; 66: 14-19.
    CrossrefPubMedGoogle Scholar
  • 7 Goldman D. Lung dysfunction in diabetes. Diabetes Care 2003; 26: 1913-1918.
    CrossrefPubMedGoogle Scholar
  • 8 Strojek K, Ziora D. Sroczyński J, Oklek K. Late lung symptoms of diabetes. Pneumonol Alergol Pol. 1993; 61: 166-170.
    PubMedGoogle Scholar
  • 9 Kuziemski K, Górska L, Słominski W, Kalicka R, Specjalski K, Adamczyk- KBąk. et al Sens of DLCO for microangiopathy diagnosis. Pneumonol Alergol Pol 2008; 76: 43A.
    PubMedGoogle Scholar
  • 10 Kuziemski K, Górska L, Jassem E, Madej-Dmochowska A. Lung microangiopathy in diabetes. Pneumonol Alergol Pol 2009; 77: 394-399.
    PubMedGoogle Scholar
  • 11 Frank A, Chuong C, Johnson R. A finite-element model of oxygen diffusion in the pulmonary capillaries. J Appl Physiol 1996; 82: 2036-2044.
    PubMedGoogle Scholar
  • 12 Hsia C, Chuong C, Johnson R. Critique of conceptual basis of diffusing capacity estimates: a finite-element analysis. J Appl Physiol 1995; 79: 1039-1047.
    CrossrefPubMedGoogle Scholar
  • 13 Federspiel W. Pulmonary diffusing capacity: implications of two-phase blond flow in capillaries. Respir Physiol 1989; 77: 119-134.
    CrossrefPubMedGoogle Scholar
  • 14 Wang E., Popel A. Effect of red blood cell shape on oxygen transport in capillaries. Math Biosci 1993; 116: 89-110.
    CrossrefPubMedGoogle Scholar
  • 15 Roughton F., Forster R. Relative importance of diffusion and chemical reaction rates in determining rate of exchange of gases in the human lung, with the special reference to true diffusing capacity of pulmonary membrane and volume of blood in the lung capillaries. J Appl Physiol 1957; 11: 290-302.
    CrossrefPubMedGoogle Scholar
  • 16 American Thoracic Society. Single-breath carbon monoxide diffusing capacity (transfer factor): recommendations for a standard technique – 1995 update. Am J Respir Crit Care Med 1995; 152: 2185-2198.
    CrossrefPubMedGoogle Scholar
  • 17 West JB. Respiratory physiology - the essentials. Philadelphia: Lippincott Williams & Wilkins; 2008.
    Google Scholar
  • 18 Marini JJ. Pressure-controlled ventilation. In Tobin MJ. editor. Principles and practice of mechanical ventilation. New York: McGraw-Hill; 1994. 305 323
    Google Scholar
  • 19 Nahum A, Marini JJ. Adjuncts to mechanical ventilation. Clin Chest Med 1996; 17: 491-411.
    CrossrefPubMedGoogle Scholar
  • 20 Taylor AE, Rehder K, Hyatt RE, Parker JC.. Clinical Respiratory Physiology. Emeryville: W.B.Saunders Company; 1989.
    Google Scholar
  • 21 Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ. et al Compendium of Physical Activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 2000; 32: 498-504.
    CrossrefPubMedGoogle Scholar
  • 22 Siggaard-Andersen O, Wimberley PD, Gothgen I, Siggaard-Andersen M. A mathematical model of the hemoglobin-oxygen dissociation curve of human blood and of the oxygen partial pressure as a function of temperature. Clinical Chemistry. 1984; 30: 1646-1651.
    PubMedGoogle Scholar
  • 23 Golec L. Dissociation of blood hemoglobin. Polish Journal of Aviation Medicine 2006; 3: 249-256.
    PubMedGoogle Scholar
  • 24 Khee-Shing ML. Configuration of the hemoglobin oxygen dissociation curve demystified: a basic mathematical proof for medical and biological sciences undergraduates. Advan Physiol Educ 2007; 31: 198-201.
    PubMedGoogle Scholar
  • 25 Lungest1000 product card [cited 2010 Oct 9]. Available from www.mes.com.pl.
    PubMedGoogle Scholar
  • 26 Nelson ME, Rejeski WJ, Blair SN, Duncan PW, Judge JO, King AC. et al. Physical activity and public health in older adults: Recommendation from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007; 8: 1435-1445.
    PubMedGoogle Scholar
  • 27 Guyton AC, Hall JE. Textbook of Medical Physiology. Philadelphia: WB Saunders Company; 1996.
    Google Scholar
  • 28 Panzer RJ, Black ER, Griner PF. Diagnostic strategies for common medical problems. Philadelphia: American College of Physicians; 1991
    PubMedGoogle Scholar