Article Text

  1. J. S. Ferguson,
  2. S. Bond,
  3. J. Guo,
  4. A. S. Delsing,
  5. J. E. Cook-Glanroth,
  6. E. A. Hoffman,
  7. G. McLennan
  1. The University of Iowa, Iowa City


Current imaging methods of the pleura include the chest roentgenogram, CT, MRI, and ultrasound. Each of these methods has limitations, but primarily is limited by the apposition of other structures near the thin pleura, and the two-dimensional images obtained with these methods. With advances in computer-aided imaging over the last decade, creation of virtual three-dimensional images of the pleural surface and space is now possible. In preliminary studies, patients with pleural disease underwent computerized tomography (CT) imaging of the thorax for clinical indications using a Toshiba Aquilon 16-slice scanner. The digital data set of images was then imported into internal analytical software labeled Pulmonary Analysis Software Suite (PASS). Using PASS, segmentation of the lung images was performed to generate a region of interest (ROI). The ROI was then converted to Hounsfield units equivalent to air to virtually remove pixels that correspond to lung tissue, leaving the pleural surface images intact. PASS was then used to volumetrically reconstruct three-dimensional images of the entire pleural surface. Abnormalities of the pleural surface, such as masses or nodules, could then be analyzed as to size, volume, shape, and contour. To begin a more detailed analysis of this method, we performed experiments in sheep. Anesthetized mechanically-ventilated sheep underwent CT imaging of the thorax using a Siemens Somatom Sensation 64 64-slice scanner with a slice thickness of 0.6 mm at 0.4 mm intervals. A pneumothorax was then induced by placing a trocar into the pleural space. Phantom objects of known size, shape, and density were placed into the pleural space and the imaging was repeated. The images were then analyzed using PASS as described above with detection of the phantom objects. The phantom objects were identified and measured using the three-dimensional images. We found that three-dimensional imaging of the pleural space allowed accurate identification and measurement of the phantom objects. Furthermore, this method allows for accurate identification of shape and edge characteristics of pleural masses not easily obtained with conventional two-dimensional imaging. Three-dimensional reconstruction of the pleura may allow for improved diagnostic imaging of this complex surface, and aid in planning diagnostic and therapeutic procedures.

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