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International Conference on Complex Systems (ICCS2006)

Relating Microscopic and Macroscopic indices of alveolar destruction in emphysema

Harikrishnan Parameswaran
Department of Biomedical Engineering, Boston University, Bos

Arnab Majumdar
Department of Biomedical Engineering, Boston University, Boston

Bela Suki
Department of Biomedical Engineering, Boston University, Boston

     Full text: Not available
     Last modified: May 12, 2006

Pulmonary emphysema is characterized by the progressive breakdown of alveolar walls resulting in impaired lung function. The presence and extent of emphysema can be determined from quantitative evaluation of structural changes either at the macroscopic or at the microscopic level. Macroscopic indices such as those obtained from CT, have the advantage that they can be measured non-invasively, while microscopic indices have been shown to be more sensitive and accurate descriptors of alveolar destruction in emphysema but can only be assessed from histological sections. In this study, we attempt to relate the area weighted mean diameter of LAA clusters (DM) from CT images to the area weighted mean diameter of airspaces (Dm) measured from histopathological sections. To this end, we use a spring network model of the lung parenchyma and mimic tissue destruction by selectively cutting springs in the network. The springs are eliminated in two ways: (a) randomly, regardless of the force they carry and (b) based on the highest force. The images of the spring network are coarse grained to obtained CT-like images. At each step the microscopic Dm and macroscopic DM are measured. We find that while for random cutting Dm is linearly related to DM, in the force based cutting the relation changes to DM =k(Dm)^(alpha), where alpha= 0.6471 + 0.0551. We conclude that there exists a strong statistical relation between microscopic and macroscopic indices of structural destruction in emphysema, which, when compared to experimental data, may provide new insight into the progressive nature of the disease.

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