High resolution propagation-based imaging system for in vivo dynamic computed tomography of lungs in small animals

We have developed an x-ray imaging system for in vivo four-dimensional computed tomography (4DCT) of small animals for pre-clinical lung investigations. Our customized laboratory facility is capable of high resolution in vivo imaging at high frame rates. Characterization using phantoms demonstrate a spatial resolution of slightly below 50 μm at imaging rates of 30 Hz, and the ability to quantify material density differences of at least 3%. We benchmark our system against existing small animal pre-clinical CT scanners using a quality factor that combines spatial resolution, image noise, dose and scan time. In vivo 4DCT images obtained on our system demonstrate resolution of important features such as blood vessels and small airways, of which the smallest discernible were measured as 55-60 μm in cross section. Quantitative analysis of the images demonstrate regional differences in ventilation between injured and healthy lungs.M. Preissner , R. P. Murrie, I. Pinar, F. Werdiger, R. P. Carnibella, G. R. Zosky, A. Fouras and S. Dubsk

DNA-PKcs modulates progenitor cell proliferation and fibroblast senescence in idiopathic pulmonary fibrosis

Published online: 29 August 2019BACKGROUND: Recent studies have highlighted the contribution of senescent mesenchymal and epithelial cells in Idiopathic Pulmonary Fibrosis (IPF), but little is known regarding the molecular mechanisms that regulate the accumulation of senescent cells in this disease. Therefore, we addressed the hypothesis that the loss of DNA repair mechanisms mediated by DNA protein kinase catalytic subunit (DNA-PKcs) in IPF, promoted the accumulation of mesenchymal progenitors and progeny, and the expression of senescent markers by these cell types. METHODS: Surgical lung biopsy samples and lung fibroblasts were obtained from patients exhibiting slowly, rapidly or unknown progressing IPF and lung samples lacking any evidence of fibrotic disease (i.e. normal; NL). The expression of DNA-Pkcs in lung tissue was assessed by quantitative immunohistochemical analysis. Chronic inhibition of DNA-PKcs kinase activity was mimicked using a highly specific small molecule inhibitor, Nu7441. Proteins involved in DNA repair (stage-specific embryonic antigen (SSEA)-4+ cells) were determined by quantitative Ingenuity Pathway Analysis of transcriptomic datasets (GSE103488). Lastly, the loss of DNA-PKc was modeled in a humanized model of pulmonary fibrosis in NSG SCID mice genetically deficient in PRKDC (the transcript for DNA-PKcs) and treated with Nu7441. RESULTS: DNA-PKcs expression was significantly reduced in IPF lung tissues. Chronic inhibition of DNA-PKcs by Nu7441 promoted the proliferation of SSEA4+ mesenchymal progenitor cells and a significant increase in the expression of senescence-associated markers in cultured lung fibroblasts. Importantly, mesenchymal progenitor cells and their fibroblast progeny derived from IPF patients showed a loss of transcripts encoding for DNA damage response and DNA repair components. Further, there was a significant reduction in transcripts encoding for PRKDC (the transcript for DNA-PKcs) in SSEA4+ mesenchymal progenitor cells from IPF patients compared with normal lung donors. In SCID mice lacking DNA-PKcs activity receiving IPF lung explant cells, treatment with Nu7441 promoted the expansion of progenitor cells, which was observed as a mass of SSEA4+ CgA+ expressing cells. CONCLUSIONS: Together, our results show that the loss of DNA-PKcs promotes the expansion of SSEA4+ mesenchymal progenitors, and the senescence of their mesenchymal progeny.David M. Habiel, Miriam S. Hohmann, Milena S. Espindola, Ana Lucia Coelho, Isabelle Jones, Heather Jones, Richard Carnibella, Isaac Pinar, Freda Werdiger and Cory M. Hogaboa

Quantification of muco-obstructive lung disease variability in mice via laboratory X-ray velocimetry

To effectively diagnose, monitor and treat respiratory disease clinicians should be able to accurately assess the spatial distribution of airflow across the fine structure of lung. This capability would enable any decline or improvement in health to be located and measured, allowing improved treatment options to be designed. Current lung function assessment methods have many limitations, including the inability to accurately localise the origin of global changes within the lung. However, X-ray velocimetry (XV) has recently been demonstrated to be a sophisticated and non-invasive lung function measurement tool that is able to display the full dynamics of airflow throughout the lung over the natural breathing cycle. In this study we present two developments in XV analysis. Firstly, we show the ability of laboratory-based XV to detect the patchy nature of cystic fibrosis (CF)-like disease in β-ENaC mice. Secondly, we present a technique for numerical quantification of CF-like disease in mice that can delineate between two major modes of disease symptoms. We propose this analytical model as a simple, easy-to-interpret approach, and one capable of being readily applied to large quantities of data generated in XV imaging. Together these advances show the power of XV for assessing local airflow changes. We propose that XV should be considered as a novel lung function measurement tool for lung therapeutics development in small animal models, for CF and for other muco-obstructive diseases.Freda Werdiger, Martin Donnelley, Stephen Dubsky, Rhiannon P. Murrie, Richard P. Carnibella, Chaminda R. Samarage ... et al

Quantification of local lung disease in rat models of CF disease and CF knockout mice

Poster session abstractWerdiger, F., Morgan, K.S., Dusbky, S., Cmielewski, P., Kitchen, M., Klein, M., Hall, C., Parsons, D., Donnelley, M

Machine learning segmentation of core and penumbra from acute stroke CT perfusion data

Introduction: Computed tomography perfusion (CTP) imaging is widely used in cases of suspected acute ischemic stroke to positively identify ischemia and assess suitability for treatment through identification of reversible and irreversible tissue injury. Traditionally, this has been done via setting single perfusion thresholds on two or four CTP parameter maps. We present an alternative model for the estimation of tissue fate using multiple perfusion measures simultaneously. Methods: We used machine learning (ML) models based on four different algorithms, combining four CTP measures (cerebral blood flow, cerebral blood volume, mean transit time and delay time) plus 3D-neighborhood (patch) analysis to predict the acute ischemic core and perfusion lesion volumes. The model was developed using 86 patient images, and then tested further on 22 images. Results: XGBoost was the highest-performing algorithm. With standard threshold-based core and penumbra measures as the reference, the model demonstrated moderate agreement in segmenting core and penumbra on test images. Dice similarity coefficients for core and penumbra were 0.38 ± 0.26 and 0.50 ± 0.21, respectively, demonstrating moderate agreement. Skull-related image artefacts contributed to lower accuracy. Discussion: Further development may enable us to move beyond the current overly simplistic core and penumbra definitions using single thresholds where a single error or artefact may lead to substantial error