Quantification of tortuosity and fractal dimension of the lung vessels in pulmonary hypertension patients.
Pulmonary hypertension (PH) can result in vascular pruning and increased tortuosity of the blood vessels. In this study we examined whether automatic extraction of lung vessels from contrast-enhanced thoracic computed tomography (CT) scans and calculation of tortuosity as well as 3D fractal dimension of the segmented lung vessels results in measures associated with PH. In this pilot study, 24 patients (18 with and 6 without PH) were examined with thorax CT following their diagnostic or follow-up right-sided heart catheterisation (RHC). Images of the whole thorax were acquired with a 128-slice dual-energy CT scanner. After lung identification, a vessel enhancement filter was used to estimate the lung vessel centerlines. From these, the vascular trees were generated. For each vessel segment the tortuosity was calculated using distance metric. Fractal dimension was computed using 3D box counting. Hemodynamic data from RHC was used for correlation analysis. Distance metric, the readout of vessel tortuosity, correlated with mean pulmonary arterial pressure (Spearman correlation coefficient: ρ = 0.60) and other relevant parameters, like pulmonary vascular resistance (ρ = 0.59), arterio-venous difference in oxygen (ρ = 0.54), arterial (ρ = -0.54) and venous oxygen saturation (ρ = -0.68). Moreover, distance metric increased with increase of WHO functional class. In contrast, 3D fractal dimension was only significantly correlated with arterial oxygen saturation (ρ = 0.47). Automatic detection of the lung vascular tree can provide clinically relevant measures of blood vessel morphology. Non-invasive quantification of pulmonary vessel tortuosity may provide a tool to evaluate the severity of pulmonary hypertension.


BACKGROUND
ClinicalTrials.gov NCT01607489.
Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria ; Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria.
Michael
M
Helmberger
Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria.
Michael
M
Pienn
Institute for Computer Graphics and Vision, Graz University of Technology, Graz, Austria ; Ludwig Boltzmann Institute for Clinical Forensic Imaging, Graz, Austria.
Martin
M
Urschler
DiagnostikZentrum Graz, Graz, Austria.
Peter
P
Kullnig
Institute for Medical Engineering, Graz University of Technology, Graz, Austria.
Rudolf
R
Stollberger
Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria ; Division of Pulmonology, Department of Internal Medicine, Medical University of Graz, Graz, Austria.
Gabor
G
Kovacs
Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria ; Experimental Anesthesiology, Department of Anesthesia and Intensive Care Medicine, Medical University of Graz, Graz, Austria.
Andrea
A
Olschewski
Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria ; Division of Pulmonology, Department of Internal Medicine, Medical University of Graz, Graz, Austria.
Horst
H
Olschewski
Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria.
Zoltán
Z
Bálint
D000328:Adult; D000368:Aged; D000792:Angiography; D001794:Blood Pressure; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D006976:Hypertension, Pulmonary / Q000000981:diagnostic imaging / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D011651:Pulmonary Artery; D014057:Tomography, X-Ray Computed