Open Access

Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

  • Jianming Liang1Email author,
  • Timo Järvi1,
  • Aaro Kiuru2,
  • Martti Kormano2 and
  • Erkki Svedström2
EURASIP Journal on Advances in Signal Processing20032003:153027

DOI: 10.1155/S1110865703212117

Received: 31 January 2002

Published: 14 April 2003

Abstract

The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT) and nuclear medicine (NM) studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

Keywords

chest images dynamic chest image analysis pulmonary perfusion perfusion model effects of contrast media

Authors’ Affiliations

(1)
Turku Centre for Computer Science, DataCity
(2)
Department of Diagnostic Radiology, Turku University

Copyright

© Copyright © 2003 Hindawi Publishing Corporation 2003