Magnetic Resonance Imaging Image Data Research Articles

Noninvasive mapping of regional response to segmental allergen challenge using magnetic resonance imaging and [F‐18]fluorodeoxyglucose positron emission tomography

Magnetic resonance (MR) and positron emission tomography (PET) imaging techniques were coregistered to demonstrate regional ventilation and inflammation in the lung for in vivo, noninvasive evaluation of regional lung function associated with allergic inflammation. Four Brown Norway rats were imaged pre- and post segmental allergen challenge using respiratory-gated He-3 magnetic resonance imaging (MRI) to visualize ventilation, T(1)-weighted proton MRI to depict inflammatory infiltrate, and [F-18]fluorodeoxyglucose-PET to detect regional glucose metabolism by inflammatory cells. Segmental allergen challenges were delivered and the pre- and postchallenge lung as well as the contralateral lung were compared. Coregistration of the imaging results demonstrated that regions of ventilation defects, inflammatory infiltrate, and increased glucose metabolism correlated well with the site of allergen challenge delivery and inflammatory cell recruitment, as confirmed by histology. This method demonstrates that fusion of functional and anatomic PET and MRI image data may be useful to elucidate the functional correlates of inflammatory processes in the lungs.

5613492 Method and product for improved images in magnetic resonance imaging using multiple breatholding

In MRI (Magnetic Resonance Imaging) the signal-to-noise images of a subject's body organs are improved by combining the signals from a number of position co-registered images or fractional data sets. The co-registration is obtained by reducing movement of the organ by the subject holding his breath. A computer cursor may be positioned at a selected point of the subject's organ displayed on the MRI monitor's screen to produce a fiducial marking on the MRI image or fractional data sets, which provides for accurate co-registration. Alternatively, a computer edge detection algorithm is used to determine the edge, and position, of the organ of interest and to produce radio frequency offsets for accurate co-registration of the subsequent images or fractional data sets. The fractional data sets, each having a fiducial marking, are combined to form a final MRI image.