Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
권호 표지
DOI QR코드

DOI QR Code

Fractal Dimension Analysis of MDCT Images for Quantifying the Morphological Changes of the Pulmonary Artery Tree in Patients with Pulmonary Hypertension

  • Haitao, Sun (Shandong University, Shandong Medical Imaging Research Institute, CT Room) ;
  • Ning, Li (Shandong University, Shandong Medical Imaging Research Institute, CT Room) ;
  • Lijun, Guo (Shandong University, Shandong Medical Imaging Research Institute, CT Room) ;
  • Fei, Gao (Shandong University, Shandong Medical Imaging Research Institute, CT Room) ;
  • Cheng, Liu (Shandong University, Shandong Medical Imaging Research Institute, CT Room)
  • Published : 2011.06.01
⟨ Previous Next ⟩

Abstract

Objective: The aim of this study was to use fractal dimension (FD) analysis on multidetector CT (MDCT) images for quantifying the morphological changes of the pulmonary artery tree in patients with pulmonary hypertension (PH). Materials and Methods: Fourteen patients with PH and 17 patients without PH as controls were studied. All of the patients underwent contrast-enhanced helical CT and transthoracic echocardiography. The pulmonary artery trees were generated using post-processing software, and the FD and projected image area of the pulmonary artery trees were determined with ImageJ software in a personal computer. The FD, the projected image area and the pulmonary artery pressure (PAP) were statistically evaluated in the two groups. Results: The FD, the projected image area and the PAP of the patients with PH were higher than those values of the patients without PH (p < 0.05, t-test). There was a high correlation of FD with the PAP (r = 0.82, p < 0.05, partial correlation analysis). There was a moderate correlation of FD with the projected image area (r = 0.49, p < 0.05, partial correlation analysis). There was a correlation of the PAP with the projected image area (r = 0.65, p < 0.05, Pearson correlation analysis). Conclusion: The FD of the pulmonary arteries in the PH patients was significantly higher than that of the controls. There is a high correlation of FD with the PAP.

Keywords

References

  1. D'Alonzo GE, Barst RJ, Ayres SM, Bergofsky EH, Brundage BH, Detre KM, et al. Survival in patients with primary pulmonary hypertension. Results from a national prospective registry. Ann Intern Med 1991;115:343-349 https://doi.org/10.7326/0003-4819-115-5-343
  2. Schannwell CM, Steiner S, Strauer BE. Diagnostics in pulmonary hypertension. J Physiol Pharmacol 2007;58 Suppl 5:591-602
  3. Arcasoy SM, Christie JD, Ferrari VA, Sutton MS, Zisman DA, Blumenthal NP, et al. Echocardiographic assessment of pulmonary hypertension in patients with advanced lung disease. Am J Respir Crit Care Med 2003;167:735-740 https://doi.org/10.1164/rccm.200210-1130OC
  4. Sciomer S, Badagliacca R, Fedele F. Pulmonary hypertension: echocardiographic assessment. Ital Heart J 2005;6:840-845
  5. Edwards PD, Bull RK, Coulden R. CT measurement of main pulmonary artery diameter. Br J Radiol 1998;71:1018-1020 https://doi.org/10.1259/bjr.71.850.10211060
  6. Heinrich M, Uder M, Tscholl D, Grgic A, Kramann B, Schafers HJ. CT scan findings in chronic thromboembolic pulmonary hypertension: predictors of hemodynamic improvement after pulmonary thromboendarterectomy. Chest 2005;127:1606-1613 https://doi.org/10.1378/chest.127.5.1606
  7. Kuriyama K, Gamsu G, Stern RG, Cann CE, Herfkens RJ, Brundage BH. CT-determined pulmonary artery diameters in predicting pulmonary hypertension. Invest Radiol 1984;19:16-22 https://doi.org/10.1097/00004424-198401000-00005
  8. Ng CS, Wells AU, Padley SP. A CT sign of chronic pulmonary arterial hypertension: the ratio of main pulmonary artery to aortic diameter. J Thorac Imaging 1999;14:270-278 https://doi.org/10.1097/00005382-199910000-00007
  9. Tan RT, Kuzo R, Goodman LR, Siegel R, Haasler GB, Presberg KW. Utility of CT scan evaluation for predicting pulmonary hypertension in patients with parenchymal lung disease. Medical College of Wisconsin Lung Transplant Group. Chest 1998;113:1250-1256 https://doi.org/10.1378/chest.113.5.1250
  10. Maggi F, Winterwerp JC. Method for computing the three-dimensional capacity dimension from two-dimensional projections of fractal aggregates. Phys Rev E Stat Nonlin Soft Matter Phys 2004;69:011405 https://doi.org/10.1103/PhysRevE.69.011405
  11. Weibel ER. Fractal geometry: a design principle for living organisms. Am J Physiol 1991;261:L361-L369
  12. Goh V, Sanghera B, Wellsted DM, Sundin J, Halligan S. Assessment of the spatial pattern of colorectal tumour perfusion estimated at perfusion CT using two-dimensional fractal analysis. Eur Radiol 2009;19:1358-1365 https://doi.org/10.1007/s00330-009-1304-y
  13. Kamiya A, Takahashi T. Quantitative assessments of morphological and functional properties of biological trees based on their fractal nature. J Appl Physiol 2007;102:2315-2323 https://doi.org/10.1152/japplphysiol.00856.2006
  14. Bankier AA, Madani A, Gevenois PA. CT quantification of pulmonary emphysema: assessment of lung structure and function. Crit Rev Comput Tomogr 2002;43:399-417
  15. Boser SR, Park H, Perry SF, Menache MG, Green FH. Fractal geometry of airway remodeling in human asthma. Am J Respir Crit Care Med 2005;172:817-823 https://doi.org/10.1164/rccm.200411-1463OC
  16. Kido S, Sasaki S. Fractal analysis for the assessment of pulmonary blood flow on chest radiographs. J Thorac Imaging 2003;18:80-86 https://doi.org/10.1097/00005382-200304000-00004
  17. Madani A, Keyzer C, Gevenois PA. Quantitative computed tomography assessment of lung structure and function in pulmonary emphysema. Eur Respir J 2001;18:720-730 https://doi.org/10.1183/09031936.01.00255701
  18. Huang W, Yen RT, McLaurine M, Bledsoe G. Morphometry of the human pulmonary vasculature. J Appl Physiol 1996;81:2123-2133 https://doi.org/10.1152/jappl.1996.81.5.2123
  19. Sciomer S, Magri D, Badagliacca R. Non-invasive assessment of pulmonary hypertension: Doppler-echocardiography. Pulm Pharmacol Ther 2007;20:135-140 https://doi.org/10.1016/j.pupt.2006.03.008
  20. Kido S, Kuriyama K, Higashiyama M, Kasugai T, Kuroda C. Fractal analysis of internal and peripheral textures of small peripheral bronchogenic carcinomas in thin-section computed tomography: comparison of bronchioloalveolar cell carcinomas with nonbronchioloalveolar cell carcinomas. J Comput Assist Tomogr 2003;27:56-61 https://doi.org/10.1097/00004728-200301000-00011
  21. Wu YT, Shyu KK, Jao CW, Wang ZY, Soong BW, Wu HM, et al. Fractal dimension analysis for quantifying cerebellar morphological change of multiple system atrophy of the cerebellar type (MSA-C). Neuroimage 2010;49:539-551 https://doi.org/10.1016/j.neuroimage.2009.07.042
  22. Lv D, Guo X, Wang X, Zhang J, Fang J. Computerized characterization of prostate cancer by fractal analysis in MR images. J Magn Reson Imaging 2009;30:161-168 https://doi.org/10.1002/jmri.21819
  23. Kim N, Seo JB, Song KS, Chae EJ, Kang SH. Semi-automatic measurement of the airway dimension by computed tomography using the full-with-half-maximum method: a study of the measurement accuracy according to the orientation of an artificial airway. Korean J Radiol 2008;9:236-242 https://doi.org/10.3348/kjr.2008.9.3.236
  24. Kim N, Seo JB, Song KS, Chae EJ, Kang SH. Semi-automatic measurement of the airway dimension by computed tomography using the full-width-half-maximum method: a study on the measurement accuracy according to the CT parameters and size of the airway. Korean J Radiol 2008;9:226-235 https://doi.org/10.3348/kjr.2008.9.3.226
  25. Haimovici JB, Trotman-Dickenson B, Halpern EF, Dec GW, Ginns LC, Shepard JA, et al. Relationship between pulmonary artery diameter at computed tomography and pulmonary artery pressures at right-sided heart catheterization. Massachusetts General Hospital Lung Transplantation Program. Acad Radiol 1997;4:327-334 https://doi.org/10.1016/S1076-6332(97)80111-0
  26. Froelich JJ, Koenig H, Knaak L, Krass S, Klose KJ. Relationship between pulmonary artery volumes at computed tomography and pulmonary artery pressures in patients with- and without pulmonary hypertension. Eur J Radiol 2008;67:466-471 https://doi.org/10.1016/j.ejrad.2007.08.022
  27. Ley S, Mereles D, Risse F, Grunig E, Ley-Zaporozhan J, Tecer Z, et al. Quantitative 3D pulmonary MR-perfusion in patients with pulmonary arterial hypertension: correlation with invasive pressure measurements. Eur J Radiol 2007;61:251-255 https://doi.org/10.1016/j.ejrad.2006.08.028
  28. Boxt LM, Katz J, Liebovitch LS, Jones R, Esser PD, Reid L. Fractal analysis of pulmonary arteries: the fractal dimension is lower in pulmonary hypertension. J Thorac Imaging 1994;9:8-13 https://doi.org/10.1097/00005382-199424000-00002
  29. Molthen RC, Karau KL, Dawson CA. Quantitative models of the rat pulmonary arterial tree morphometry applied to hypoxiainduced arterial remodeling. J Appl Physiol 2004;97:2372-2384 https://doi.org/10.1152/japplphysiol.00454.2004
  30. Fernandez E, Jelinek HF. Use of fractal theory in neuroscience: methods, advantages, and potential problems. Methods 2001;24:309-321 https://doi.org/10.1006/meth.2001.1201
  31. Kassab GS. Scaling laws of vascular trees: of form and function. Am J Physiol Heart Circ Physiol 2006;290:H894-H903 https://doi.org/10.1152/ajpheart.00579.2005

Cited by

  1. Magnetic Resonance and Computed Tomography Imaging of the Structural and Functional Changes of Pulmonary Arterial Hypertension vol.28, pp.3, 2013, https://doi.org/10.1097/rti.0b013e31828d5c48
  2. Quantification of Tortuosity and Fractal Dimension of the Lung Vessels in Pulmonary Hypertension Patients vol.9, pp.1, 2011, https://doi.org/10.1371/journal.pone.0087515
  3. Optimality, cost minimization and the design of arterial networks vol.10, pp.None, 2011, https://doi.org/10.1016/j.artres.2015.01.001
  4. Imaging in Chronic Thromboembolic Pulmonary Hypertension vol.32, pp.2, 2011, https://doi.org/10.1097/rti.0000000000000256
  5. EUS elastography (strain ratio) and fractal-based quantitative analysis for the diagnosis of solid pancreatic lesions vol.87, pp.6, 2011, https://doi.org/10.1016/j.gie.2017.12.031
  6. Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease vol.11, pp.None, 2020, https://doi.org/10.3389/fphys.2020.603197
  7. Application of Fractal Analysis to Evaluate the Rat Brain Arterial System vol.65, pp.3, 2011, https://doi.org/10.1134/s0006350920030100
  8. An index of the fractal characteristic of an airway tree is associated with airflow limitations and future body mass index reduction in COPD patients vol.128, pp.5, 2011, https://doi.org/10.1152/japplphysiol.00461.2019
  9. Fractal analysis of concurrently prepared latex rubber casts of the bronchial and vascular systems of the human lung vol.10, pp.7, 2011, https://doi.org/10.1098/rsob.190249
  10. Quantification of Arterial and Venous Morphologic Markers in Pulmonary Arterial Hypertension Using CT Imaging vol.160, pp.6, 2011, https://doi.org/10.1016/j.chest.2021.06.069