PULMO

Pulmo automatically detects the lungs in CT volume scans and analyses the density distribution of the lungs. In follow-up studies, lung densitometry can quantify the loss of lung tissue associated with emphysema but also other lung diseases that affect the density of the lungs. By identifying different partitions of the lungs with equal sub-volumes, one can assess the CT parameters for each partition. This allows a more localized quantification of progression of lung diseases and the quantification of the distribution of emphysema.
The software is used in numerous reference sites for assessing the effects of drugs treatment in large clinical trials.
Advantages of Pulmo are the ability to assist diagnosis, improve therapy planning for lung volume reduction surgery and monitoring with respect to accuracy and time effort.

Method

Basically, the software package consists of four parts:

• Calibration. The densities in the images are recalibrated by rescaling these densities depending upon the measured density of the blood in the patient and of air outside of the patient. By this calibration procedure, changes in the spectrum of the X-ray tube, due to tube ageing, and changes in the patient's blood density, due the emphysema, are taken into account. The measurement of the mean blood density is carried out by a semi-automatic detection of the largest artery, the aorta, and by calculating the mean density value within this region, with the lowest standard error.
• (Semi-)automatic selection of the lungs. The lungs are selected automatically by having the user select a location within the trachea (which is automatically suggested by the program). Subsequently, the software carries out a so-called region growing, which lets this initial location expand (like a balloon) until it reaches the borders of the lungs. The septum (the border between the left and right lung), the trachea and the carina are detected separately. The lung parenchyma is defined by excluding the septa, trachea and large vessels from the initial segmentation result. By doing so, the lungs are selected with a high degree of reproducibility. A number of editing tools have been developed to facilitate user-friendly procedures for correcting the contours; after editing the program checks the resulting contours for inconsistencies.
• Calculation and analysis of the density distributions. The histograms of the left and right lung parenchyma are calculated. From these histograms seven parameters are derived: the total lung volume, mean lung density, the lung weight (which is equal to the product of volume and density), the n-th percentile point (as described above), the area of the lungs (in %) below a certain density value, called the relative area, the heterogeneity of the density over the different partitions and the locality of the emphysema (basal vs apical).
• Presentation of the results. Finally, the results are presented to the user, and can be saved on disk to facilitate further statistical analysis by spreadsheet programs or statistical packages.

Developments

• Pulmonary Embolism module. An extension will provide the quantitative assessment of the bronchial tree and quantification of pulmonary embolism that will measure the pulmonary density, which is an indirect measurement of the consequences pulmonary embolism or its treatment.
• Reference normal database. Lung density should not only be calculated but also be compared to normal healthy lung densities. By generating graphic reports of a T-score, the results of individual patients can be interpreted and general clinical feasibility for emphysema quantification will arise.
• Asthma, chronic bronchitis. Automatic assessment of bronchial dimensions.

Publications

Please download the complete list in PDF format here.

Posters

• Stoel BC, Putter H, Stolk J, Bakker ME, Dirksen A, Stockley RA, Piitulainen E, Russi EW, Reiber JHC.
  Volume Correction in CT Densitometry in Follow-up Studies on Pulmonary Emphysema: Results From SPREAD.
  Poster
• Stoel BC, Bakker ME, Stolk J, Dirksen A, Stockley RA, Piitulainen E, Russi EW, Reiber JHC.
  Comparison of Five Different CT Scanners in Their Ability to Measure Emphysema Progression: A Phantom Study.
  Poster
• Bakker ME, Stoel BC, Stolk J, Putter H, Dirksen A, Stockley RA, Piitulainen E, Russi EW, Reiber JHC.
  Inter- and intra-observer variability in the densitometric assessment of pulmonary emphysema with computed tomography.
  Poster