Elsevier

Medical Image Analysis

Volume 12, Issue 6, December 2008, Pages 752-763
Medical Image Analysis

Registration-based estimates of local lung tissue expansion compared to xenon CT measures of specific ventilation

https://doi.org/10.1016/j.media.2008.03.007Get rights and content

Abstract

The main function of the respiratory system is gas exchange. Since many disease or injury conditions can cause biomechanical or material property changes that can alter lung function, there is a great interest in measuring regional lung ventilation and regional specific volume change. We describe a registration-based technique for estimating local lung expansion from multiple respiratory-gated CT images of the thorax. The degree of regional lung expansion is measured using the Jacobian (a function of local partial derivatives) of the registration displacement field, which we show is directly related to specific volume change. We compare the ventral–dorsal patterns of lung expansion estimated across five pressure changes to a xenon CT based measure of specific ventilation in five anesthetized sheep studied in the supine orientation. Using 3D image registration to match images acquired at 10 cm H2O and 15 cm H2O airway pressures gave the best match between the average Jacobian and the xenon CT specific ventilation (linear regression, average r2=0.73).

Introduction

The main function of the respiratory system is gas exchange. Regional ventilation depends on the mechanical relationships between the lungs, rib cage, diaphragm, and abdomen, which work together to generate expansile forces. Since many disease or injury conditions can change lung material properties, lung mechanics, and lung function, it is useful to understand both the global and local functional behavior of lungs.

Regional ventilation and regional lung strain have been measured directly and indirectly with a variety of invasive techniques (Hoffman et al., 1983a, Hubmayr et al., 1983, Robertson et al., 1997), with radioisotope imaging (Milic-Emili et al., 1966, Bunow et al., 1979, van der Mark et al., 1984), with X-ray computed tomography (CT) (Hoffman et al., 1983b, Hoffman et al., 1995, Hoffman and Ritman, 1985, Tajik et al., 2002, Chon et al., 2005, Chon et al., 2007), and with hyperpolarized gas magnetic resonance (MR) imaging (Wild et al., 2003, Woodhouse et al., 2005, Altes et al., 2006, Patz et al., 2007). Invasive methods, such as percutaneously or surgically implanted parenchymal markers or inhaled fluorescent microspheres, are not possible to translate to humans. Radioisotope imaging, such as scintigraphy, single photon emission CT (SPECT), and positron emission tomography (PET), can provide a direct functional assessment of ventilation, but nuclear medicine imaging has low spatial resolution, and to obtain reasonable signal to noise ratios, one must usually image across many respiratory cycles, further reducing image resolution. Hyperpolarized gas MR imaging can image ventilation with sufficient temporal resolution so that the dynamics of gas flow patterns through the lung can be observed. Lung microstructure, such as alveolar size, can also be indirectly assessed using MR through the use of the so-called “apparent diffusion coefficient”. However, lung MR is currently only partially quantitative, does not depict much anatomic detail, and requires special equipment to hyperpolarize the gas used during imaging. CT imaging can provide high-resolution images of the lung, but this high spatial resolution usually comes at the cost of low temporal resolution (relative to the speed of gas transport in the airspaces) and/or limited spatial coverage. And while CT can produce excellent anatomic images, standard CT imaging does not typically provide for functional assessment.

Xenon-enhanced CT (Xe-CT) is a non-invasive method for the measurement of regional pulmonary ventilation. With Xe-CT, radiodense, non-radioactive xenon gas is inhaled and exhaled during imaging, and local ventilation time constants are calculated by observing the gas wash-in and wash-out rates on serial CT images (Simon and Marcucci, 1998, Marcucci et al., 2001, Tajik et al., 2002, Chon et al., 2005, Chon et al., 2007). Xenon gas provides enhancement on the CT proportional to the concentration of xenon in the region being imaged; enhancements as much as 150–200 Hounsfield units (HU) are possible with high concentrations of xenon (Marcucci et al., 2001, Tajik et al., 2002, Chon et al., 2005, Chon et al., 2007). Xe-CT is not without shortcomings. Xe-CT requires the use of expensive xenon gas and the associated hardware to control gas delivery. Additional hardware is needed if one wishes to harvest the expired gas for recycling during a re-breathing study. In addition, it is known that xenon gas has a strong anesthetic effect that must be carefully monitored. Finally, Xe-CT imaging protocols require high temporal resolution imaging, so axial coverage is usually limited. Z-axis coverage with modern multi-detector scanners currently ranges from about 2.5 to 12 cm, but the typical z-axis extent of the human lung is on the order of 25 cm. Nonetheless, recent work with the Xe-CT technique has re-established the interest in these methods for measuring regional ventilation. When combined with the unique capability of CT to describe lung anatomic detail, Xe-CT can provide detailed information on lung structure and respiratory function (Hoffman et al., 2003).

Imaging has long been used to study lung mechanics, and some investigators have studied the linkage between estimates of regional lung expansion and local lung ventilation (Hoffman et al., 1983a, Hoffman et al., 1986, Rodarte et al., 1985, Hubmayr et al., 1987, Guerrero et al., 2005, Guerrero et al., 2006, Sundaram and Gee, 2005). Sundaram and Gee (2005) have applied serial magnetic resonance imaging to the problem of studying lung mechanics. Using static breath-hold imaging they acquired a single sagittal cross-section of the lung at different inflations. Using non-linear image registration, they estimated a dense displacement field from one image to the other, and from the displacement field they computed regional lung strain. Guerrero et al., 2005, Guerrero et al., 2006 used two CT images, acquired at different lung inflations, and optical flow image registration to estimate regional ventilation to identify functioning vs. non-functioning lung tissue for radiotherapy treatment planning. While they were able to show a close correlation with global measurements of lung ventilation, their experimental methods did not allow them to compare local estimates of lung expansion with regional lung ventilation. Christensen et al. (2007) used image registration to match images across cine-CT sequences, and estimate rates of local tissue expansion and contraction. Their measurements matched well with spirometry data, but they were not able to compare the registration-based measurements to local measures of regional tissue ventilation.

We describe a technique that uses multiple respiratory-gated CT images of the lung acquired at different levels of inflation, along with 3D image registration, to make local estimates of lung tissue expansion. We compare these lung expansion estimates to Xe-CT derived measures of regional ventilation to validate our measurements and establish their physiological significance. The ability to estimate regional ventilation maps for the entire lung from quickly and easily obtained respiratory-gated images is a significant contribution to functional lung imaging because of the potential increase in resolution, and large reductions in imaging time, radiation, and contrast agent exposure. The image registration also provides estimates of directional tissue strains, which may yield insights into the mechanics of regional ventilation.

Section snippets

Methods

Fig. 1 shows a block diagram of the entire process. Two or more respiratory-gated data sets are gathered at different points in the respiratory cycle, reflecting the state of the lung at two different volumes (and therefore, pressures). 3D image registration is used to create a voxel-by-voxel displacement map that shows the motion of the lung tissue as a function of respiratory state. The Jacobian of the displacement field is calculated for each voxel in the lung and is used to represent local

Registration accuracy

Registration accuracy was first visually assessed by examining anatomic landmarks in the registered images. Fig. 6a and b shows coronal slices from the P0 and P25 images for one animal. Fig. 6c shows a coronal view of the P0 image transformed to match the P25 image, and shows good anatomic correspondence. The differences in grayscale intensity between Fig. 6b and c are due to the increased air content (and hence, decreased CT density) at the 25 cm H2O pressure.

Fig. 7a and b shows the projection

Discussion

Fig. 8a and b shows that for four of the five animals, the average marker registration error for the 5 cm H2O step size pairs was small (less than 1.5 mm) as assessed by the manually-defined landmarks. The outlier, animal AS60150, shows large registration errors when matching the P0 image to P5 image. Upon further inspection, it was determined that the AS60150 case had significant edema and atelectasis in the most dorsal lung regions, greatly reducing the contrast between the vessels, airway

Summary and conclusions

We have described a registration-based technique for estimating local lung expansion from multiple respiratory-gated CT images of the thorax. The degree of lung expansion is measured using the Jacobian of the registration displacement field. The Jacobian map is shown to be proportional to local specific volume change, a physiologically meaningful parameter that can be used to assess the functional capacity of lung tissue.

Our registration results show that in four of the five animals we have

Acknowledgements

The authors would like to thank Mr. Matthew Fuld and Mr. Ahmed Halaweish for their assistance with the animal experiments, and Dr. Deokiee Chon for his advice concerning the Xe-CT analysis. This work was supported in part by grants HL079406, HL064368, and EB004126 from the National Institutes of Health. A preliminary version of this manuscript appeared in Reinhardt et al. (2007).

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