Most medical imaging is inherently three-dimensional (3D) but for validation of pathological
findings, histopathology is commonly used and typically histopathology images are acquired as twodimensional
slices with quantitative analysis performed in a single dimension. Histopathology is
invasive, labour-intensive, and the analysis cannot be performed in real time, yet it remains the gold
standard for the pathological diagnosis and validation of clinical or radiological diagnoses of disease.
A major goal worldwide is to improve medical imaging resolution, sensitivity and specificity to
better guide therapy and biopsy and to one day delay or replace biopsy. A key limitation however is
the lack of tools to directly compare 3D macroscopic imaging acquired in patients with
histopathology findings, typically provided in a single dimension (1D) or in two dimensions (2D).
To directly address this, we developed methods for 2D histology slice visualization/registration to
generate 3D volumes and quantified tissue components in the 3D volume for direct comparison to
volumetric micro-CT and clinical CT. We used the elastase-instilled mouse emphysema lung model
to evaluate our methods with murine lungs sectioned (5 μm thickness/10 μm gap) and digitized with
2μm in-plane resolution. 3D volumes were generated for wildtype and elastase mouse lung sections
after semi-automated registration of all tissue slices. The 1D mean linear intercept (Lm) for wildtype
(WT) (47.1 μm ± 9.8 μm) and elastase mouse lung (64.5 μm ± 14.0 μm) was significantly different
(p<.001). We also generated 3D measurements based on tissue and airspace morphometry from the
3D volumes and all of these were significantly different (p<.0001) when comparing elastase and WT
mouse lung. The ratio of the airspace-to-lung volume for the entire lung volume was also
significantly and strongly correlated with Lm.
KEYWORDS: Image segmentation, Magnetic resonance imaging, Lung, 3D metrology, Chronic obstructive pulmonary disease, 3D image processing, 3D acquisition, Algorithm development, Image registration, Image processing algorithms and systems
A semi-automated method for generating hyperpolarized helium-3 (3He) measurements of individual slice (2D) or whole
lung (3D) gas distribution was developed. 3He MRI functional images were segmented using two-dimensional (2D) and
three-dimensional (3D) hierarchical K-means clustering of the 3He MRI signal and in addition a seeded region-growing
algorithm was employed for segmentation of the 1H MRI thoracic cavity volume. 3He MRI pulmonary function
measurements were generated following two-dimensional landmark-based non-rigid registration of the 3He and 1H
pulmonary images. We applied this method to MRI of healthy subjects and subjects with chronic obstructive lung
disease (COPD). The results of hierarchical K-means 2D and 3D segmentation were compared to an expert observer's
manual segmentation results using linear regression, Pearson correlations and the Dice similarity coefficient. 2D
hierarchical K-means segmentation of ventilation volume (VV) and ventilation defect volume (VDV) was strongly and
significantly correlated with manual measurements (VV: r=0.98, p<.0001; VDV: r=0.97, p<.0001) and mean Dice
coefficients were greater than 92% for all subjects. 3D hierarchical K-means segmentation of VV and VDV was also
strongly and significantly correlated with manual measurements (VV: r=0.98, p<.0001; VDV: r=0.64, p<.0001) and the
mean Dice coefficients were greater than 91% for all subjects. Both 2D and 3D semi-automated segmentation of 3He
MRI gas distribution provides a way to generate novel pulmonary function measurements.
Hyperpolarized helium-3 (3He) magnetic resonance imaging (MRI) has emerged as a non-invasive research method for
quantifying lung structural and functional changes, enabling direct visualization in vivo at high spatial and temporal
resolution. Here we described the development of methods for quantifying ventilation dynamics in response to
salbutamol in Chronic Obstructive Pulmonary Disease (COPD). Whole body 3.0 Tesla Excite 12.0 MRI system was
used to obtain multi-slice coronal images acquired immediately after subjects inhaled hyperpolarized 3He gas.
Ventilated volume (VV), ventilation defect volume (VDV) and thoracic cavity volume (TCV) were recorded following
segmentation of 3He and 1H images respectively, and used to calculate percent ventilated volume (PVV) and ventilation
defect percent (VDP). Manual segmentation and Otsu thresholding were significantly correlated for VV (r=.82, p=.001),
VDV (r=.87 p=.0002), PVV (r=.85, p=.0005), and VDP (r=.85, p=.0005). The level of agreement between these
segmentation methods was also evaluated using Bland-Altman analysis and this showed that manual segmentation was
consistently higher for VV (Mean=.22 L, SD=.05) and consistently lower for VDV (Mean=-.13, SD=.05) measurements
than Otsu thresholding. To automate the quantification of newly ventilated pixels (NVp) post-bronchodilator, we used
translation, rotation, and scaling transformations to register pre-and post-salbutamol images. There was a significant
correlation between NVp and VDV (r=-.94 p=.005) and between percent newly ventilated pixels (PNVp) and VDP (r=-
.89, p=.02), but not for VV or PVV. Evaluation of 3He MRI ventilation dynamics using Otsu thresholding and
landmark-based image registration provides a way to regionally quantify functional changes in COPD subjects after
treatment with beta-agonist bronchodilators, a common COPD and asthma therapy.
KEYWORDS: Magnetic resonance imaging, Lung, Cystic fibrosis, Image analysis, Image segmentation, Visualization, Signal to noise ratio, Pulmonary disorders, MATLAB, Medicine
We developed image analysis tools to evaluate spatial and temporal 3He magnetic resonance imaging (MRI) ventilation
in asthma and cystic fibrosis. We also developed temporal ventilation probability maps to provide a way to describe and
quantify ventilation heterogeneity over time, as a way to test respiratory exacerbations or treatment predictions and to
provide a discrete probability measurement of 3He ventilation defect persistence.
KEYWORDS: Magnetic resonance imaging, Image segmentation, Lung, Helium, Medical research, Spirometry, Image analysis, Image visualization, Chest, Signal to noise ratio
We examined subjects with exercise-induced asthma to assess the short-term reproducibility of hyperpolarized (Hp)
helium-3 (3He) magnetic resonance imaging (MRI) of regional ventilation defects before asthma exacerbation. Our
objective was to evaluate pre-exercise interscan Hp 3He MRI measurement reproducibility of subjects scanned on three
separate occasions (5 ± 2 days between sessions). Magnetic resonance imaging was performed at 3.0 Tesla with a
custom-built rigid elliptical 3He chest coil. Images for six subjects were evaluated by two observers; one who quantified
ventilation defect score and ventilation defect volume and another who quantified percent ventilated volume. For all six
subjects, pre-exercise ventilation defect location and number of defects were similar at all three visits suggesting
persistence of many defects, but changes in defect volume and percent ventilated volume were detected.
Technological advances in micro-CT scanners have introduced dynamic, flat-panel scanners, which allow the acquisition of volume images in a few seconds. However, motion artefacts associated with normal respiratory motion arise when imaging the thorax or abdomen. To reduce these artefacts and the accompanying loss of spatial resolution, and to enable the study of rodent respiratory function, we developed a retrospective respiratory gating technique for volume micro-CT imaging of free-breathing rodents.
Anaesthetized male C57BL6 mice were placed in the prone position on a custom-made bed containing an embedded pressure chamber that was connected to a pressure transducer. Inhalation motion caused an increase in the chamber pressure, which was monitored as a surrogate for the respiratory waveform, and measured throughout the scan.
Projection images of the mouse thorax were acquired using a GE Locus Ultra micro-CT scanner, at 80 kVp, 50 mA (entrance exposure of approximately 2.7 cGy per rotation), over ten rotations in less than 1 minute. Respiratory gating was performed retrospectively by selecting projections that were obtained during the same portion of the respiratory cycle prior to reconstruction; CT images reconstructed from three to ten rotations were evaluated. The nominal voxel spacing was 0.15 mm isotropic.
Images were assessed for image noise, artefacts and measurement accuracy of physiologically relevant structures. These measurements showed no significant differences for images reconstructed from projection images from five to ten rotations. The optimum number of rotations for imaging mouse lungs was found to be six, corresponding to a 30 second (16.2 cGy) scan.
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