3D image analysis allows us to describe blood vessel structures. Furthermore, we can distinguish between regular and affected vessels. These findings help to improve potential therapeutic options.

Capillary Vascular Structures

A variety of obstructive diseases is associated with a loss of lung tissue. In general, the human lung cannot compensate for this loss of tissue. This is different in rodents and smaller animals: E.g., the lung of mice completely regains its original capacity by compensatory growth within 21 days after resection of approximately 40% of the lung tissue. Transferring this behavior to the human lung would greatly improve therapeutic options in many lung diseases.

Microvascular corrosion casts synchrotron-radiation X-ray tomographic images of microvascular corrosion casts. To gain deeper insight into this regeneration process, the topology of the vascular system is studied based on synchrotron-radiation X-ray tomographic images of microvascular corrosion casts. Based on the Euler number, intussusceptive pillars indicating growth can be detected automatically for the first time.

Growth of Murine Lungs — Geometrical Description Based on High Resolution Synchrotron Tomography
 

A variety of diseases of the human lung lead to loss of lung tissue. In general, the adult human lung cannot compensate for such a loss. However, mice are able to compensate for this loss of tissue by growing new lung tissue. The remaining tissue grows until the original lung volume is reached. This process is known as compensatory lung growth. Investigating this process could greatly improve therapeutic options for humans in the future.

 

In particular, we study the morphology of the blood vessel system on capillary level for different growing states. The research group of Professor Konerding at the Institute of Functional and Clinical Anatomy at Johannes Gutenberg University Mainz has started to investigate image data of mouse lungs in context of an NIH project. Besidehistological sections they also generated micro computed tomographic (CT) imagedata.

In this phd thesis we aim a quantitative analysis of the available μ CT data. First, we have to develop new algorithms to segment the relevant structures. In a second step, we have to identify geometric parameters to model the growing process. To estimate these parameters based on 3D CT images, the resulting algorithms have to be implemented.

The results of this analysis should be used to develop a mathematical model describing the process of lung growth in mice.
 

Advisors:

Publications:

  • S. Föhst, W. Wagner, M. Ackermann, C. Redenbach, K.Schladitz, O. Wirjadi, A. B. Ysasi, S. J. Mentzer, M. A. Konerding:
    3D Image Analytical Detection of Intussusceptive Pillars in Murine Lung.
    Journal of Microscopy 260, (3), pp. 326-337, (2015).
Ausschnitt der 3D-Rekonstruktion eines CT-Bildes der kapillaren Blutgefäße einer Mauselunge.
© Photo ITWM

Excerpt of a μ-CT scan of intessusceptive pillars in a murine lung. Resolution: 650 nm.