MOTIVATION: The lobes of the lungs slide relative to each other during breathing. Quantifying lobar sliding can aid in
better understanding lung function, better modeling of lung dynamics, and a better understanding of the limits of image
registration performance near fissures. We have developed a method to estimate lobar sliding in the lung from image
registration of CT scans.
METHODS: Six human lungs were analyzed using CT scans spanning functional residual capacity (FRC) to total lung
capacity (TLC). The lung lobes were segmented and registered on a lobe-by-lobe basis. The displacement fields from the
independent lobe registrations were then combined into a single image. This technique allows for displacement
discontinuity at lobar boundaries. The displacement field was then analyzed as a continuum by forming finite elements
from the voxel grid of the FRC image. Elements at a discontinuity will appear to have undergone significantly elevated
'shear stretch' compared to those within the parenchyma. Shear stretch is shown to be a good measure of sliding
magnitude in this context.
RESULTS: The sliding map clearly delineated the fissures of the lung. The fissure between the right upper and right
lower lobes showed the greatest sliding in all subjects while the fissure between the right upper and right middle lobe
showed the least sliding.
Radiation induced pulmonary diseases can change the tissue material properties of lung parenchyma and the
mechanics of the respiratory system. Recent advances in multi-detector-row CT (MDCT), 4DCT respiratory
gating methods, and image processing techniques enable us to follow and measure those changes noninvasively
during radiation therapy at a regional level. This study compares the 4DCT based ventilation measurement with
the results from hyperpolarized helium-3 MR using the cumulative distribution function maps and the relative
overlap (RO) statistic. We show that the similarity between the two measurements increases as the increase of
the B-Spline grid spacing and Laplacian weighting which result a smoother ventilation map. The best similarity
is found with weighting of 0.5 for linear elasticity and B-Spline grid spacing of 32 mm. Future work is to improve
the lung image registration algorithm by incorporating hyperpolarized helium-3 MR information so as to improve
its physiological modeling of the lung tissue deformation.
In registration-based analyses of lung biomechanics and function, high quality registrations are essential to obtain
meaningful results. Various criteria have been suggested to find the correspondence mappings between two lung
images acquired at different levels of inflation. In this paper, we describe a new metric, the sum of squared
vesselness measure difference (SSVMD), that utilizes the rich information of blood vessel locations and matches
similar vesselness patterns in two images. Preserving both the lung tissue volume and the vesselness measure,
a registration algorithm is developed to minimize the sum of squared tissue volume difference (SSTVD) and
SSVMD together. We compare the registration accuracy using SSTVD + SSVMD with that using SSTVD
alone by registering lung CT images of three normal human subjects. After adding the new SSVMD metric, the
improvement of registration accuracy is observed by landmark error and fissure positioning error analyses. The
average values of landmark error and fissure positioning error are reduced by about 30% and 25%, respectively.
The mean landmark error is on the order of 1 mm. Statistical testing of landmark errors shows that there
is a statistically significant difference between two methods with p values < 0.05 in all three subjects. Visual
inspection shows there are obvious accuracy improvements in the lung regions near the thoracic cage after adding
SSVMD.
The lungs undergo expansion and contraction during the respiratory cycle. Since many disease or injury conditions
are associated with the biomechanical or material property changes that can alter lung function, there is a
great interest in measuring regional lung ventilation and regional mechanical changes. We describe a technique
that uses multiple respiratory-gated CT images and non-rigid 3D image registration to make local estimates
of lung tissue expansion. The degree of regional lung expansion is measured using the Jacobian (a function
of local partial derivatives) of the registration displacement field. We compare the ventral-dorsal patterns of
lung expansion estimated in both retrospectively reconstructed dynamic scans and static breath-hold scans to
a xenon CT based measure of specific ventilation and a semi-automatic reference standard in four anesthetized
sheep studied in the supine orientation. The regional lung expansion estimated by 3D image registration of
images acquired at 50% and 75% phase points of the inspiratory portion of the respiratory cycle and 20 cm H2O
and 25 cm H2O airway pressures gave the best match between the average Jacobian and the xenon CT specific
ventilation respectively (linear regression, average r2 = 0.85 and r2 = 0.84). The registration accuracy assessed
by 200 semi-automatically matched landmarks in both the dynamic and static scans show landmark error on the
order of 2 mm.
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