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Magnetic resonance lung function – a breakthrough for lung imaging and functional assessment? A phantom study and clinical trial

Maren Zapke1*, Hans-Georg Topf1, Martin Zenker1, Rainer Kuth2, Michael Deimling2, Peter Kreisler2, Manfred Rauh1, Christophe Chefd'hotel3, Bernhard Geiger3 and Thomas Rupprecht4

  • * Corresponding author: Maren Zapke mnwagner@gmx.de

  • † Equal contributors

Author Affiliations

1 University Children's Hospital, University Erlangen-Nuremberg, Loschgestr. 15, 91054 Erlangen, Germany

2 Siemens medical solutions, Henkestr. 127; 91052 Erlangen, Germany

3 Siemens Corporate Research; 755 College Road East, Princeton, NJ 08540-6632, USA

4 Children's Hospital; Preuschwitzer Straße 101, D-95445 Bayreuth, Germany

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Respiratory Research 2006, 7:106  doi:10.1186/1465-9921-7-106

Published: 6 August 2006

Abstract

Background

Chronic lung diseases are a major issue in public health. A serial pulmonary assessment using imaging techniques free of ionizing radiation and which provides early information on local function impairment would therefore be a considerably important development. Magnetic resonance imaging (MRI) is a powerful tool for the static and dynamic imaging of many organs. Its application in lung imaging however, has been limited due to the low water content of the lung and the artefacts evident at air-tissue interfaces. Many attempts have been made to visualize local ventilation using the inhalation of hyperpolarized gases or gadolinium aerosol responding to MRI. None of these methods are applicable for broad clinical use as they require specific equipment.

Methods

We have shown previously that low-field MRI can be used for static imaging of the lung. Here we show that mathematical processing of data derived from serial MRI scans during the respiratory cycle produces good quality images of local ventilation without any contrast agent. A phantom study and investigations in 85 patients were performed.

Results

The phantom study proved our theoretical considerations. In 99 patient investigations good correlation (r = 0.8; p ≤ 0.001) was seen for pulmonary function tests and MR ventilation measurements. Small ventilation defects were visualized.

Conclusion

With this method, ventilation defects can be diagnosed long before any imaging or pulmonary function test will indicate disease. This surprisingly simple approach could easily be incorporated in clinical routine and may be a breakthrough for lung imaging and functional assessment.