A semi-automatic framework of measuring pulmonary arterial metrics at anatomic airway locations using CT imaging

Dakai Jin; Junfeng Guo; Timothy M Dougherty; Krishna S Iyer; Eric A Hoffman; Punam K Saha

doi:10.1117/12.2216558

Back

Journal article

A semi-automatic framework of measuring pulmonary arterial metrics at anatomic airway locations using CT imaging

Dakai Jin, Junfeng Guo, Timothy M Dougherty, Krishna S Iyer, Eric A Hoffman and Punam K Saha

Proceedings of SPIE, the international society for optical engineering, Vol.9788, pp.978816-978816-6

02/27/2016

DOI: 10.1117/12.2216558

PMCID: PMC5327735

PMID: 28250572

Files and links (1)

url

https://www.ncbi.nlm.nih.gov/pmc/articles/5327735View

Open Access

Abstract

Pulmonary vascular dysfunction has been implicated in smoking-related susceptibility to emphysema. With the growing interest in characterizing arterial morphology for early evaluation of the vascular role in pulmonary diseases, there is an increasing need for the standardization of a framework for arterial morphological assessment at airway segmental levels. In this paper, we present an effective and robust semi-automatic framework to segment pulmonary arteries at different anatomic airway branches and measure their cross-sectional area (CSA). The method starts with user-specified endpoints of a target arterial segment through a custom-built graphical user interface. It then automatically detect the centerline joining the endpoints, determines the local structure orientation and computes the CSA along the centerline after filtering out the adjacent pulmonary structures, such as veins or airway walls. Several new techniques are presented, including collision-impact based cost function for centerline detection, radial sample-line based CSA computation, and outlier analysis of radial distance to subtract adjacent neighboring structures in the CSA measurement. The method was applied to repeat-scan pulmonary multirow detector CT (MDCT) images from ten healthy subjects (age: 21–48 Yrs, mean: 28.5 Yrs; 7 female) at functional residual capacity (FRC). The reproducibility of computed arterial CSA from four airway segmental regions in middle and lower lobes was analyzed. The overall repeat-scan intra-class correlation (ICC) of the computed CSA from all four airway regions in ten subjects was 96% with maximum ICC found at LB10 and RB4 regions.

computed tomography

radial sample line

minimum cost path

cross sectional area

airway tree

Pulmonary artery

Details

Title: Subtitle: A semi-automatic framework of measuring pulmonary arterial metrics at anatomic airway locations using CT imaging
Creators: Dakai Jin - Dept. of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
Junfeng Guo - Dept. of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
Timothy M Dougherty - Dept. of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
Krishna S Iyer - Dept. of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
Eric A Hoffman - Dept. of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
Punam K Saha - Dept. of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
Resource Type: Journal article
Publication Details: Proceedings of SPIE, the international society for optical engineering, Vol.9788, pp.978816-978816-6
DOI: 10.1117/12.2216558
PMID: 28250572
PMCID: PMC5327735
NLM abbreviation: Proc SPIE Int Soc Opt Eng
ISSN: 0277-786X
eISSN: 1996-756X
Language: English
Date published: 02/27/2016
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Internal Medicine
Record Identifier: 9984051560002771

Metrics

27 Record Views

3 Times Cited - Web of Science