Chronic obstructive pulmonary disease (COPD), manifested as emphysema and chronic airway obstruction, can be exacerbated by bacterial and viral infections. Although the frequency of exacerbations increases as the disease progresses, the mechanisms underlying this phenomenon are largely unknown, and there is a need for a simple in vivo exacerbation model. In this study, we compared four groups of mice treated with PBS alone, elastase alone, LPS alone, and elastase plus LPS. A single intratracheal administration of LPS to mice with elastase-induced emphysema provoked infiltration of inflammatory cells, especially CD8(+) T cells, into alveolar spaces and increased matrix metalloproteinase-9, tissue inhibitor of metalloproteinase-1, and perforin production in bronchoalveolar lavage fluid at the acute inflammatory phase compared with the other groups. We also measured the percentage of low-attenuation area (LAA%) in the above mice using micro-computed X-ray tomography. The LAA% was the most sensitive parameter for quantitative assessments of emphysema among all the parameters evaluated. Using the parameter of LAA%, we found significantly more severe alveolar destruction in the group treated with elastase plus LPS compared with the other groups during long-term longitudinal observations. We built three-dimensional images of the emphysema and confirmed that the lungs of elastase plus LPS-treated mice contained larger emphysematous areas than mice treated with elastase alone. Although human exacerbation of COPD is clinically and pathologically complicated, this simple mouse model mimics human cases to some extent and will be useful for elucidating its mechanism and developing therapeutic strategies.

https://www.atsjournals.org/doi/pdf/10.1165/rcmb.2013-0074OC

A Single Dose of Lipopolysaccharide into Mice with Emphysema Mimics Human Chronic Obstructive Pulmonary Disease Exacerbation as Assessed by Micro-Computed Tomography

As one of the most prevalent chronic disorders, airway disease is a major cause of morbidity and mortality worldwide. In order to understand its underlying mechanisms and to enable assessment of therapeutic efficacy of a variety of possible interventions, noninvasive investigation of the airways in a large number of subjects is of great research interest. Due to its high resolution in temporal and spatial domains, computed tomography (CT) has been widely used in clinical practices for studying the normal and abnormal manifestations of lung diseases, albeit there is a need to clearly demonstrate the benefits in light of the cost and radiation dose associated with CT examinations performed for the purpose of airway analysis. Whereas a single CT examination consists of a large number of images, manually identifying airway morphological characteristics and computing features to enable thorough investigations of airway and other lung diseases is very time-consuming and susceptible to errors. Hence, automated and semiautomated computerized analysis of human airways is becoming an important research area in medical imaging. A number of computerized techniques have been developed to date for the analysis of lung airways. In this review, we present a summary of the primary methods developed for computerized analysis of human airways, including airway segmentation, airway labeling, and airway morphometry, as well as a number of computer-aided clinical applications, such as virtual bronchoscopy. Both successes and underlying limitations of these approaches are discussed, while highlighting areas that may require additional work.

/pdf/ct-based-computerized-identification-and-analysis-of-human-4guw8cd1xu.pdf

CT based computerized identification and analysis of human airways: A review

To define the sensitivity of microcomputed tomography- (micro-CT-) derived descriptors for the quantification of lung damage caused by elastase instillation. Materials and Methods. The lungs of 30 elastase treated and 30 control A/J mice were analyzed 1, 6, 12, and 24 hours and 7 and 17 days after elastase instillation using (i) breath-hold-gated micro-CT, (ii) pulmonary function tests (PFTs), (iii) RT-PCR for RNA cytokine expression, and (iv) histomorphometry. For the latter, an automatic, parallel software toolset was implemented that computes the airspace enlargement descriptors: mean linear intercept (Lm) and weighted means of airspace diameters (D0, D1, and D2). A Support Vector Classifier was trained and tested based on three nonhistological descriptors using D2 as ground truth. Results. D2 detected statistically significant differences (P < 0.01) between the groups at all time points. Furthermore, D2 at 1 hour (24 hours) was significantly lower (P < 0.01) than D2 at 24 hours (7 days). The classifier trained on the micro-CT-derived descriptors achieves an area under the curve (AUC) of 0.95 well above the others (PFTS AUC = 0.71; cytokine AUC = 0.88). Conclusion. Micro-CT-derived descriptors are more sensitive than the other methods compared, to detect in vivo early signs of the disease.

/pdf/quantification-of-lung-damage-in-an-elastase-induced-mouse-2t6cih9ezz.pdf

Quantification of lung damage in an elastase-induced mouse model of emphysema

Purpose:
Small animal micro-CT imaging is being used increasingly in preclinical biomedical research to provide phenotypic descriptions of genomic models. Most of this imaging is coincident with animal death and is used to show the extent of disease as an end point. Longitudinal imaging overcomes the limitation of single time-point imaging because it enables tracking of the natural history of disease and provides qualitative and, where possible, quantitative assessments of the effects of an intervention. The pulmonary system is affected by many disease conditions, such as lung cancer, chronic obstructive pulmonary disease, asthma, and granulomatous disorders. Noninvasive imaging can accurately assess the lung phenotype within the living animal, evaluating not only global lung measures, but also regional pathology. However, imaging the lung in the living animal is complicated by rapid respiratory motion, which leads to image based artifacts. Furthermore, no standard mouse lung imaging protocols exist for longitudinal assessment, with each group needing to develop their own systematic approach.

Methods:
In this article, the authors present an outline for performing longitudinal breath-hold gated micro-CT imaging for the assessment of lung nodules in a mouse model of lung cancer. The authors describe modifications to the previously published intermittent isopressure breath-hold technique including a new animal preparation and anesthesia protocol, implementation of a ring artifact reduction, variable scanner geometry, and polynomial beam hardening correction. In addition, the authors describe a multitime-point data set registration and tumor labeling and tracking strategy.

Results:
In vivo micro-CT data sets were acquired at months 2, 3, and 4 posturethane administration in cancer mice (n=5) and simultaneously in control mice (n=3). 137 unique lung nodules were identified from the cancer mice while no nodules were detected in the control mice. A total of 411 nodules were segmented and labeled over the three time-points. Lung nodule metrics including RECIST, Ortho, WHO, and 3D volume were determined and extracted. A tumor incidence rate of 30.44±1.93 SEM for n=5 was found with identification of nodules as small as 0.11 mm (RECIST) and as large as 1.66 mm (RECIST). In addition, the tumor growth and doubling rate between months 2–3 and 3–4 were calculated. Here, the growth rate was slightly higher in the second period based on the 3D volume data (0.12±0.13 to 0.13±0.17μl) but significantly less based on the linear diameter metrics [RECIST (0.33±0.19 to 0.17±0.18mm); Ortho (0.24±0.15 to 0.16±0.15mm)], indicating the need to understand how each metric is obtained and how to correctly interpret change in tumor size.

Conclusions:
In conclusion, micro-CT imaging provides a unique platform forin vivo longitudinal assessment of pulmonary lung cancer progression and potentially tracking of therapies at very high resolutions. The ability to evaluate the same subject over time provides for a sensitive assay that can be carried out on a smaller sample size. When integrated with image processing and analysisroutines as detailed in this study, the data acquired from micro-CT imaging can now provide a very powerful assessment of pulmonary disease outcomes.

/pdf/longitudinal-assessment-of-lung-cancer-progression-in-the-qjco8deeup.pdf

Longitudinal assessment of lung cancer progression in the mouse using in vivo micro-CT imaging.

X-ray Computed Tomography (CT) is one of the most commonly utilized anatomical imaging modalities for both research and clinical purposes. CT combines high-resolution, three-dimensional data with relatively fast acquisition to provide a solid platform for non-invasive human or specimen imaging. The primary limitation of CT is its inability to distinguish many soft tissues based on native contrast. While bone has high contrast within a CT image due to its material density from calcium phosphate, soft tissue is less dense and many are homogenous in density. This presents a challenge in distinguishing one type of soft tissue from another. A couple exceptions include the lungs as well as fat, both of which have unique densities owing to the presence of air or bulk hydrocarbons, respectively. In order to facilitate X-ray CT imaging of other structures, a range of contrast agents have been developed to selectively identify and visualize the anatomical properties of individual tissues. Most agents incorporate atoms like iodine, gold, or barium because of their ability to absorb X-rays, and thus impart contrast to a given organ system. Here we review the strategies available to visualize lung, fat, brain, kidney, liver, spleen, vasculature, gastrointestinal tract, and liver tissues of living mice using either innate contrast, or commercial injectable or ingestible agents with selective perfusion. Further, we demonstrate how each of these approaches will facilitate the non-invasive, longitudinal, in vivo imaging of pre-clinical disease models at each anatomical site.

In vivo X-Ray Computed Tomographic Imaging of Soft Tissue with Native, Intravenous, or Oral Contrast

Animal models of lung disease are gaining importance in understanding the underlying mechanisms of diseases such as emphysema and lung cancer. Micro-CT allows in vivo imaging of these models, thus permitting the study of the progression of the disease or the effect of therapeutic drugs in longitudinal studies. Automated analysis of micro-CT images can be helpful to understand the physiology of diseased lungs, especially when combined with measurements of respiratory system input impedance. In this work, we present a fast and robust murine airway segmentation and reconstruction algorithm. The algorithm is based on a propagating fast marching wavefront that, as it grows, divides the tree into segments. We devised a number of specific rules to guarantee that the front propagates only inside the airways and to avoid leaking into the parenchyma. The algorithm was tested on normal mice, a mouse model of chronic inflammation and a mouse model of emphysema. A comparison with manual segmentations of two independent observers shows that the specificity and sensitivity values of our method are comparable to the inter-observer variability, and radius measurements of the mainstem bronchi reveal significant differences between healthy and diseased mice. Combining measurements of the automatically segmented airways with the parameters of the constant phase model provides extra information on how disease affects lung function.

/pdf/airway-segmentation-and-analysis-for-the-study-of-mouse-1a7r96mv9t.pdf

G de Biurrun

Papers

Airway segmentation and analysis for the study of mouse models of lung disease using micro-CT.