Heterologous matrix metalloproteinase gene promoter activity allows In Vivo real-time imaging of Bleomycin-induced Lung fibrosis in transiently transgenized mice

Idiopathic pulmonary fibrosis is a very common interstitial lung disease derived from chronic inflammatory insults, characterized by massive scar tissue deposition that causes the progressive loss of lung function and subsequent death for respiratory failure.Bleomycin is used as the standard agent to induce experimental pulmonary fibrosis in animal models for the study of its pathogenesis. However, to visualize the establishment of lung fibrosis after treatment, the animal sacrifice is necessary. Thus, the aim of this study was to avoid this limitation by using an innovative approach based on a double bleomycin treatment protocol, along with the in vivo images analysis of bleomycintreated mice. A reporter gene construct, containing the luciferase open reading frame under the matrix metalloproteinase-1 promoter control region, was tested on doublebleomycin-treated mice to investigate, in real time, the correlation between bleomycin treatment, inflammation, tissue remodeling and fibrosis. Bioluminescence emitted by the lungs of bleomycin-treated mice, corroborated by fluorescent molecular tomography, successfully allowed real time monitoring of fibrosis establishment. The reporter gene technology experienced in this work could represent an advanced functional approach for real time non-invasive assessment of disease evolution during therapy, in a reliable and translational living animal model.Fil: Stellari, Fabio Franco. Chiese Farmaceutici; ItaliaFil: Ruscitti, Francesca. Chiese Farmaceutici; ItaliaFil: Pompilio, Daniela. Chiese Farmaceutici; ItaliaFil: Ravanetti, Francesca. Università di Parma. Dipartimento di Scienze Medico Veterinarie; ItaliaFil: Tebaldi, Giulia. Università di Parma. Dipartimento di Scienze Medico Veterinarie; ItaliaFil: Macchi, Francesca. Università di Parma. Dipartimento di Scienze Medico Veterinarie; ItaliaFil: Verna, Andrea Elizabeth. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Chiese Farmaceutici; ItaliaFil: Villetti, Gino. Chiese Farmaceutici; ItaliaFil: Donofrio, Gaetano. Università di Parma. Dipartimento di Scienze Medico Veterinarie ; Itali

Improved correction for the tissue fraction effect in lung PET/CT imaging

Recently, there has been an increased interest in imaging different pulmonary disorders using PET techniques. Previous work has shown, for static PET/CT, that air content in the lung influences reconstructed image values and that it is vital to correct for this 'tissue fraction effect' (TFE). In this paper, we extend this work to include the blood component and also investigate the TFE in dynamic imaging. CT imaging and PET kinetic modelling are used to determine fractional air and blood voxel volumes in six patients with idiopathic pulmonary fibrosis. These values are used to illustrate best and worst case scenarios when interpreting images without correcting for the TFE. In addition, the fractional volumes were used to determine correction factors for the SUV and the kinetic parameters. These were then applied to the patient images. The kinetic parameters K1 and Ki along with the static parameter SUV were all found to be affected by the TFE with both air and blood providing a significant contribution to the errors. Without corrections, errors range from 34-80% in the best case and 29-96% in the worst case. In the patient data, without correcting for the TFE, regions of high density (fibrosis) appeared to have a higher uptake than lower density (normal appearing tissue), however this was reversed after air and blood correction. The proposed correction methods are vital for quantitative and relative accuracy. Without these corrections, images may be misinterpreted

Modeling Progressive Fibrosis with Pluripotent Stem Cells Identifies an Anti-fibrotic Small Molecule.

Progressive organ fibrosis accounts for one-third of all deaths worldwide, yet preclinical models that mimic the complex, progressive nature of the disease are lacking, and hence, there are no curative therapies. Progressive fibrosis across organs shares common cellular and molecular pathways involving chronic injury, inflammation, and aberrant repair resulting in deposition of extracellular matrix, organ remodeling, and ultimately organ failure. We describe the generation and characterization of an in vitro progressive fibrosis model that uses cell types derived from induced pluripotent stem cells. Our model produces endogenous activated transforming growth factor β (TGF-β) and contains activated fibroblastic aggregates that progressively increase in size and stiffness with activation of known fibrotic molecular and cellular changes. We used this model as a phenotypic drug discovery platform for modulators of fibrosis. We validated this platform by identifying a compound that promotes resolution of fibrosis in in vivo and ex vivo models of ocular and lung fibrosis

Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage.

Tissue fibrosis is a major cause of mortality that results from the deposition of matrix proteins by an activated mesenchyme. Macrophages accumulate in fibrosis, but the role of specific subgroups in supporting fibrogenesis has not been investigated in vivo. Here, we used single-cell RNA sequencing (scRNA-seq) to characterize the heterogeneity of macrophages in bleomycin-induced lung fibrosis in mice. A novel computational framework for the annotation of scRNA-seq by reference to bulk transcriptomes (SingleR) enabled the subclustering of macrophages and revealed a disease-associated subgroup with a transitional gene expression profile intermediate between monocyte-derived and alveolar macrophages. These CX3CR1+SiglecF+ transitional macrophages localized to the fibrotic niche and had a profibrotic effect in vivo. Human orthologs of genes expressed by the transitional macrophages were upregulated in samples from patients with idiopathic pulmonary fibrosis. Thus, we have identified a pathological subgroup of transitional macrophages that are required for the fibrotic response to injury

Quantitative CT analysis in ILD and use of artificial intelligence on imaging of ILD

Advances in computer technology over the past decade, particularly in the field of medical image analysis, have permitted the identification, characterisation and quantitation of abnormalities that can be used to diagnose disease or determine disease severity. On CT imaging performed in patients with ILD, deep-learning computer algorithms now demonstrate comparable performance with trained observers in the identification of a UIP pattern, which is associated with a poor prognosis in several fibrosing ILDs. Computer tools that quantify individual voxel-level CT features have also come of age and can predict mortality with greater power than visual CT analysis scores. As these tools become more established, they have the potential to improve the sensitivity with which minor degrees of disease progression are identified. Currently, PFTs are the gold standard measure used to assess clinical deterioration. However, the variation associated with pulmonary function measurements may mask the presence of small but genuine functional decline, which in the future could be confirmed by computer tools. The current chapter will describe the latest advances in quantitative CT analysis and deep learning as related to ILDs and suggest potential future directions for this rapidly advancing field

Positron emision [i.e. emission] tomography (PET) in non-malignant chest diseases

Molecular imaging is a functional imaging that identify disease in its earliest stages and determine the exact location of metabolically active tissue such as tumours. Often before symptoms occur or abnormalities can be detected with other diagnostic tests. Two simultaneous studies to explore the potentials of Positron Emission tomography (PET) have been conducted. In the first study, the role of PET in pulmonary drug deposition has been evaluated whereas in the second study, it’s potential in monitoring disease progression and treatment response monitoring in IPF has been discovered.Gamma imaging such as planer and Single Photon Emission computed tomography (SPECT) have been used for decades in the imaging of pulmonary drug deposition, despite numerous advantage of PET very few studies were found in the literature. Two studies were conducted using in-house developed lung surrogate phantom and Andersen cascade impactor to demonstrate PET role in pulmonary drug deposition. The lung surrogate phantom study is a ‘’proof of concept’’ in which series of experiments was conducted leading to the development of a usable model. Each experimental procedure was conducted repeatedly over time to reduce the level of experimental errors. To my knowledge, this is the first phantom experiment quantifying the deposition pattern of aerosolized [18F]-FDG while mimicking human tidal breathing. In a separate experiment the Andersen cascade impactor (ACI) have been used to measure distribution of beclometasone dipropionate (BDP), formoterol fumarate dihydrate (FFA) as well as [18F]-2-fluorp-2-deoxy-D-glucose ([18F]-FDG) along the stages of ACI.The overall activity deposition within the phantom; cylinder and the extra-pulmonary section of the tube were 8.07 ± 3.51MBq. The deposition within the cylinder (lung surrogate) was 6.27 ± 2.55MBq. The average total internal dose (phantom cylinders and the extra-pulmonary section of the tube was calculated to be 0.2mSv/PET scan. These results are expected in human clinical trial under similar experimental conditions.The Aerodynamic particle size distribution (APSD) along the fractionating part of the AIM comprises of large particle mass (LPM) and small particle mass (SPM). The LPM is APSD >5μg deposited on stage 1 (representing to upper respiratory tract), whereas, the SPM comprised of the particle size 1-5 μg and < 1 μg deposited on stage 2 (representing the small airways and lung parenchyma) and an exhalation filter. In general, the deposition of the drugs and [18F]-FDG within the fractionating part of the impactor was predominantly within 1-5μg, which is a desirable fine particle fraction (FPF) of the active pharmaceutical ingredients (API) leading to pulmonary deposition.The potentials of PET imaging in pulmonary drug deposition has been demonstrated in these experiments using lung surrogate phantom and cascade impactor. [18F]-FDG PET imaging has the potentials in providing better understanding of regional distribution of pulmonary drug deposition. Standardization of these methods will enable PET imaging to be used in pulmonary drug development.In the second study, A retrospective studies using PET data was carried out to measure uptake of [18F]-FDG in the region of apparently normal lung in IPF. This was compared to normal control lung images to ascertain differences in their uptake value.HRCT is the current gold standard imaging the diagnosis of IPF. Recently there is growing interest in exploring the potentials of PET imaging in the disease progression and treatment response monitoring in IPF.Patients with IPF that had undergone PET-CT imaging for investigation of concomitant cancer diagnosis were identified retrospectively in a single interstitial lung disease (ILD) tertiary referral centre. Non IPF patients that had a PET-CT scan in the same centre for cancer diagnosis without non-malignant lung disease were identified to form two control groups: a lung cancer control group and a control group with no evidence of intra-thoracic disease (extra-thoracic malignancy controls). These two control groups were identified to allow assessment of whether the presence of thoracic malignancy effected [18F]-FDG uptake. In the event of no effect being identified, a pooled analysis comparing IPF patients and all controls was planned.No difference in standard uptake value (SUV) Maximum (Max) and SUV mean uptake was observed in the mean of 4 (Region of Interest) ROIs between lung cancer controls and extra-thoracic malignancy controls in all 3 normalizations (SUV Max body weight (BW), SUV body surface area (BSA) and SUV activity concentration (AC)) and therefore data from these groups were pooled for comparison with IPF patients. The SUV Max and SUV mean of radiologically normal lung in IPF patients was significantly higher than the normal lung in controls. However, the CT number/Hounsfield unit of the IPF patients and the control group are comparable. In addition, 20 textural features were identified in each ROI both in CT and PET data sets. Five out of the twenty CT textural features shows significant differences between the 2 controls as such, they were excluded. Fifteen were pooled together for comparison with IPF patients. Five out of the fifteen CT textural features shows significant differences when compared with IPF and all are consistent with five features that shows significant difference in PET dataset.Increase [18F]-FDG PET signal within areas of areas of apparently normal lung parenchyma has been demonstrated using SUV with 3 different normalization methods as well as using textural feature analysis. These findings have shown the heterogeneous nature of the disease process indicating the possibility of the disease activity within the apparently normal lung CT lung images. These finding may provide insight into the pathogenesis of the disease and may be helpful in monitoring the disease progression and treatment response

Filtration-histogram based texture analysis and CALIPER based pattern analysis as quantitative CT techniques in idiopathic pulmonary fibrosis: head-to-head comparison

OBJECTIVE: To assess the prognostic performance of two quantitative CT (qCT) techniques in idiopathic pulmonary fibrosis (IPF) compared to established clinical measures of disease severity (GAP index). METHODS: Retrospective analysis of high-resolution CT scans for 59 patients (age 70.5 ± 8.8 years) with two qCT methods. Computer-aided lung informatics for pathology evaluation and ratings based analysis classified the lung parenchyma into six different patterns: normal, ground glass, reticulation, hyperlucent, honeycombing and pulmonary vessels. Filtration histogram-based texture analysis extracted texture features: mean intensity, standard deviation (SD), entropy, mean of positive pixels (MPPs), skewness and kurtosis at different spatial scale filters. Univariate Kaplan-Meier survival analysis assessed the different qCT parameters' performance to predict patient outcome and refine the standard GAP staging system. Multivariate cox regression analysis assessed the independence of the significant univariate predictors of patient outcome. RESULTS: The predominant parenchymal lung pattern was reticulation (16.6% ± 13.9), with pulmonary vessel percentage being the most predictive of worse patient outcome (p = 0.009). Higher SD, entropy and MPP, in addition to lower skewness and kurtosis at fine texture scale (SSF2), were the most significant predictors of worse outcome (p < 0.001). Multivariate cox regression analysis demonstrated that SD (SSF2) was the only independent predictor of survival (p < 0.001). Better patient outcome prediction was achieved after adding total vessel percentage and SD (SSF2) to the GAP staging system (p = 0.006). CONCLUSION: Filtration-histogram texture analysis can be an independent predictor of patient mortality in IPF patients. ADVANCES IN KNOWLEDGE: qCT analysis can help in risk stratifying IPF patients in addition to clinical markers

Improved In vivo Assessment of Pulmonary Fibrosis in Mice using X-Ray Dark-Field Radiography

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung disease with a median life expectancy of 4-5 years after initial diagnosis. Early diagnosis and accurate monitoring of IPF are limited by a lack of sensitive imaging techniques that are able to visualize early fibrotic changes at the epithelial-mesenchymal interface. Here, we report a new x-ray imaging approach that directly visualizes the air-tissue interfaces in mice in vivo. This imaging method is based on the detection of small-angle x-ray scattering that occurs at the air-tissue interfaces in the lung. Small-angle scattering is detected with a Talbot-Lau interferometer, which provides the so-called x-ray dark-field signal. Using this imaging modality, we demonstrate-for the first time-the quantification of early pathogenic changes and their correlation with histological changes, as assessed by stereological morphometry. The presented radiography method is significantly more sensitive in detecting morphological changes compared with conventional x-ray imaging, and exhibits a significantly lower radiation dose than conventional x-ray CT. As a result of the improved imaging sensitivity, this new imaging modality could be used in future to reduce the number of animals required for pulmonary research studies

Recent advances in understanding idiopathic pulmonary fibrosis

Despite major research efforts leading to the recent approval of pirfenidone and nintedanib, the dismal prognosis of idiopathic pulmonary fibrosis (IPF) remains unchanged. The elaboration of international diagnostic criteria and disease stratification models based on clinical, physiological, radiological, and histopathological features has improved the accuracy of IPF diagnosis and prediction of mortality risk. Nevertheless, given the marked heterogeneity in clinical phenotype and the considerable overlap of IPF with other fibrotic interstitial lung diseases (ILDs), about 10% of cases of pulmonary fibrosis remain unclassifiable. Moreover, currently available tools fail to detect early IPF, predict the highly variable course of the disease, and assess response to antifibrotic drugs. Recent advances in understanding the multiple interrelated pathogenic pathways underlying IPF have identified various molecular phenotypes resulting from complex interactions among genetic, epigenetic, transcriptional, post-transcriptional, metabolic, and environmental factors. These different disease endotypes appear to confer variable susceptibility to the condition, differing risks of rapid progression, and, possibly, altered responses to therapy. The development and validation of diagnostic and prognostic biomarkers are necessary to enable a more precise and earlier diagnosis of IPF and to improve prediction of future disease behaviour. The availability of approved antifibrotic therapies together with potential new drugs currently under evaluation also highlights the need for biomarkers able to predict and assess treatment responsiveness, thereby allowing individualised treatment based on risk of progression and drug response. This approach of disease stratification and personalised medicine is already used in the routine management of many cancers and provides a potential road map for guiding clinical care in IPF