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

• Bakker ME, Stolk J, Putter H, Shaker SB, Parr DG, Piitulainen E, Russi EW, Dirksen A, Stockley RA, Reiber JHC, Stoel BC.
  Variability in Densitometric Assessment of Pulmonary Emphysema With Computed Tomography.
  Invest Radiol 2005; 40: 777-783
• Dirksen A, Dijkman JH, Madsen F, Stoel B, Hutchison DC, Ulrik C, Skovgaard L, Kok-Jensen A, Rudolphus A, Seersholm N, Vrooman HA, Reiber JH, Hansen NC, Heckscher T, Viskum K, Stolk J.
  A randomized clinical trial of alpha(1)-antitrypsin augmentation therapy.
  Am J Respir Crit Care Med 1999; 160: 1468-1472
• Parr DG, Stoel BC, Stolk J, Nightingale PG, Stockley RA.
  Influence of Calibration on Densitometric Studies of Emphysema Progression Using Computed Tomography.
  Am J Respir Crit Care Med 2004; 170: 1172-1178
• Parr DG, Stoel BC, Stolk J, Stockley RA.
  Validation of computed tomographic lung densitometry for monitoring emphysema in α1-antitrypsin deficiency.
  Thorax 2006; 61:485–490.
• Parr DG, Stoel BC, Stolk J, Stockley RA.
  Pattern of Emphysema Distribution in 1-antitrypsin Deficiency Influences Lung Function Impairment.
  Am J Respir Crit Care Med 2004; 170: 883-890.
• Shaker SB, Stavngaard T, Stolk J, Stoel BC, Dirksen A.
  α1-Antitrypsin   deficiency. 7: Computed tomographic imaging in α1-antitrypsin deficiency.
  Thorax 2004; 59: 986–991.
• Stoel BC, Vrooman HA, Stolk J, Reiber JHC.
  Sources of error in lung densitometry with CT.
  Invest Radiol 1999; 34:303-309
• Stoel BC, Stolk J.
  Optimization and Standardization of Lung Densitometry in the Assessment of Pulmonary Emphysema.
  Invest Radiol 2004; 39:681-688
• Stoel BC, Bakker ME, Stolk J, Dirksen A, Stockley RA, Piitulainen E, Russi E, Reiber JHC.
  Comparison of the sensitivities of 5 different computed tomography scanners for the assessment of the progression of pulmonary emphysema: a phantom study.
  Invest Radiol 2004; 39:1-7.
• Stolk J, Versteegh MI, Montenij LJ, Bakker ME, Grebski E, Tutic M,
  Wildermuth S, Weder W, el Bardiji M, Reiber JH, Rabe JF, Russi EW, Stoel BC
  Densitometry for assessment of effect of lung volume reduction surgery for emphysema
  Eur Respir J 2007; 29: 1138–1143
• Stolk J,  Putter H,  Bakker EM,  Saher  B,  Shaker SB,  Parr DG, Piitulainen E,  Russi EW,   Grebski E, Dirksen A, Stockley RA, Reiber JH, Stoel BC.
  Progression parameters for emphysema: A clinical investigation
  Respir Med. 2007 17; 1924-1930. 
• Stolk J, Zagers R, Vrooman HA, Aarts NJM, Schultze Kool LJ, Dijkman JH, Voorthuisen AE van, Reiber JHC.
  Assessment of the progression of emphysema by quantitative analysis of spirometrically-gated CT images.
  Eur Respir Rev 1997; 7 (43): 154-158
• Stolk J, Dirksen A, van der Lugt AA, Hutsebaut J, Mathieu J, de Ree J, Reiber JH, Stoel BC.
  Repeatability of lung density measurements with low-dose computed tomography in subjects with alpha-1-antitrypsin deficiency-associated emphysema.
  Invest Radiol 2001; 36:648-651
• Stolk J, Ng, WH, Bakker ME, Reiber JHC, Rabe KF, Putter H, Stoel BC.
  Correlation between Annual Change in Health Status and Computer Tomography Derived Lung Density in Subjects with 1-antitrypsin Deficiency.
  Thorax 2003; 58:1027-1030
• Zagers H, Vrooman HA, Aarts NJM, Stolk J, Kool LJS, Dijkman JH, VanVoorthuisen E, Reiber JHC.
  Assessment of the progression of emphysema by quantitative analysis of spirometrically gated computed tomography images.
  Invest Radiol 1996; 31: 761-767

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