MRI assessment of lung parenchymal motion in normal mice and transgenic mice with sickle cell disease.

PURPOSE: To test the feasibility of a method to quantify regional pulmonary parenchymal motion via nonrigid registration algorithm at small animal scales. MATERIALS AND METHODS: Voxel-wise displacement vector field maps were generated between end-inspiratory and end-expiratory coronal thoracic MR images on normal mice (N = 5) to analyze the magnitude and direction of parenchymal motion in the segmented regions. The analysis was repeated before and after short-term exposure to hypoxia to demonstrate the effect of hypoxia on the respiratory motion in transgenic (Tg) mice with sickle cell disease (SCD) (N = 4). RESULTS: Normal mice revealed that the right and left lungs moved symmetrically but that there was greater movement in the lower regions than in the upper regions. Calculated strain was uniform in the entire lung. In the Tg mice, the pulmonary motion before hypoxia was similar to that observed in the normal mice. Upon exposure to hypoxia, the displacement magnitude reduced and the direction of motion in some areas became distorted. CONCLUSION: MR quantification of pulmonary motion was feasible in mice and the principle that the method could detect mechanical abnormalities due to pathologic changes was proven. Quantification of pulmonary motion has the potential to lead to earlier disease diagnosis and better monitoring of disease treatments.

Towards a model of lung biomechanics: pulmonary kinematics via registration of serial lung images.

The lungs are highly elastic organs, composed of a variety of structures: vasculature, airways and parenchyma. The unique mechanical properties of each of these structures form the composite material of the lung. Numerous pulmonary diseases affect these material properties. Clinically, these structural changes cannot be directly quantified. However, medical imaging modalities such as computed tomography and magnetic resonance imaging can be used to observe lung morphology. It would be helpful to be able to correlate regional morphological changes with changes in pulmonary function. We present an approach toward the quantification of pulmonary deformation via non-rigid registration of serial MR images of the lung using the variational framework implemented in the Insight toolkit. Conventional registration methods, as exemplified by a finite element implementation of the classic elastic matching technique, are shown to perform well over a set of vascular landmarks in the measurement of lung motion. This performance is maintained in an augmented system, which combines inhomogeneous material properties with the use of domain discretizations tailored to reflect the apparent geometry within the image and to reduce background effects. These adaptations lay the groundwork for biomechanical modeling of the lung using the finite element method.

Towards a dynamic model of pulmonary parenchymal deformation: evaluation of methods for temporal reparameterization of lung data.

We approach the problem of temporal reparameterization of dynamic sequences of lung MR images. In earlier work, we employed capacity-based reparameterization to co-register temporal sequences of 2-D coronal images of the human lungs. Here, we extend that work to the evaluation of a ventilator-acquired 3-D dataset from a normal mouse. Reparameterization according to both deformation and lung volume is evaluated. Both measures provide results that closely approximate normal physiological behavior, as judged from the original data. Our ultimate goal is to be able to characterize normal parenchymal biomechanics over a population of healthy individuals, and to use this statistical model to evaluate lung deformation under various pathological states.

Characterization of regional pulmonary mechanics from serial magnetic resonance imaging data.

RATIONALE AND OBJECTIVES: The aim of this study was to investigate a method for quantifying lung motion from the registration of successive images in serial magnetic resonance imaging acquisitions during normal respiration. MATERIALS AND METHODS: Estimates of pulmonary motion were obtained by summing the normalized cross-correlation over serially acquired lung images to identify corresponding locations between the images. The estimated motions were modeled as deformations of an elastic body and thus reflect to a first order approximation the true physical behavior of lung parenchyma. The Lagrangian strain, derived from the calculated motion fields, were used to quantify the tissue deformation induced in the lung over the serial acquisition. RESULTS: The method was validated on a magnetic resonance imaging study, for which breath-hold images were acquired of a healthy volunteer at different phases of the respiratory cycle. Regional parenchymal strain was observed to be oriented toward the pulmonary hilum, with strain magnitude maximal at the midcycle of the expiratory phase. CONCLUSION: In vivo magnetic resonance imaging quantification of lung motion holds the potential of providing a new diagnostic dimension in the assessment of pulmonary function, augmenting the information provided by studies of ventilation and perfusion.