Indoor and outdoor air pollution are the 4
leading risk factors, respectively, for disability-adjusted life years worldwide [
], and exposure is associated with increased risk of pneumonia in children, respiratory cancers, and development of Chronic Obstructive Pulmonary Disease [
]. Airborne particulate matter [
] with an aerodynamic diameter of <2.5 μm (PM
) is considered particularly harmful as the small size allows inhalation deep into the lungs [
Development of a biomarker that acts as a surrogate marker of exposure could obviate the need for costly and intensive exposure monitoring. Ideally a biomarker should be: closely associated with exposure, adequately sensitive and specific, consistent across heterogenous populations, cost efficient, acceptable to the user population, and feasible for use in the field (including low-resource settings) [
The phagocytic action of airway macrophages (AM) may provide the basis for a biomarker of PM exposure. The particulate load within AM is: increased in individuals who report exposure to household air pollution compared to those who do not [
]; statistically different between individuals who use different types of domestic fuel [
]; and associated with exposure to outdoor PM in commuters who cycle in London [
]. Correlation between AM particulate load (AMPL) and worsening lung function supports a possible pathophysiological role [
]. A recent systematic review of studies calculating AMPL concluded that this biomarker is suitable for assessing personal exposure to PM, but that technical improvements are needed before this method is suitable for widespread use [
Once cell monolayers (Cytospins™) have been obtained from induced sputum (IS) or bronchoalveolar lavage (BAL) samples, several different digital image analysis software programmes can be used to calculate AMPL. ImageJ software (
, superseding a similar software, Scion Image) and Image SXM software [
) have both been used for this purpose [
There is no previously reported objective comparison of their feasibility and it is unknown whether these two methods provide comparable results. Unlike ImageJ, Image SXM has only been used with samples obtained via BAL, a technique that is not suitable for widespread use in the field due to the expertise, risks and financial costs involved. This study therefore aimed to provide an objective assessment of the relative feasibilities – with regard to resources, expertise and time required - of ImageJ and Image SXM for use with IS samples, and their comparative accuracy.
A biomarker which can be used in the field to assess an individual’s air pollution exposure will be a valuable tool for research into the health effects and benefits of interventions. In our pilot work for the Cooking and Pneumonia Study (
) we identified the need for a biomarker representative of household air pollution exposure [
]. This study set out to explore the feasibility of using IS samples for assessment of AMPL as a potential biomarker.
Although the procedure was well-tolerated by all participants who underwent IS, there was a low appointment attendance rate despite multiple appointments being offered at their convenience. This may be due to participant’s availability, but may also reflect an unwillingness to undergo the procedure suggesting that IS may not be acceptable to the wider community. A third of participants were unable to produce adequate samples. These factors resulted in a small samples size, a major limitation of this study, but also reflects a potential limitation in the feasibility of using IS as a biomarker.
The time taken for the Image SXM method was substantially lengthened by the need to manually edit images prior to analysis to improve accuracy. This editing is not required when using this software with BAL samples, which tend to have few other cells or debris.
ImageJ was the quicker method for image acquisition and analysis (median 51 min). Image capturing software used in this study for the ImageJ method delayed this process by approximately 15 min, but was not used for the Image SXM method – a limitation of this study due to the lack of available equipment. However, when combined with the time taken for sputum induction and processing (usually >90 min), this process is unlikely to be feasible for widespread use in large studies given the total time required (>2 h per participant).
Both methods require considerable expenditure for clinical and laboratory equipment. Previously published studies using ImageJ method report using a microscope with a x100 objective, while the Image SXM method requires a x40 objective, both with digital image acquisition capabilities. In this study a x60 objective was used for the ImageJ method, as greater magnification was not available with digital image capturing capabilities. Although this may have theoretically reduced the accuracy of the ImageJ methodology in our study, we experienced no difficulties visualising particulate matter within the macrophages and still found ImageJ to be the more reliable of the two methods for detecting PM. As we do not comment on the accuracy of the ImageJ method in comparison to a gold standard assessment of exposure, this limitation of our study does not have a major impact on our findings. However, it does emphasise the need for specialised equipment, which has implications for feasibility.
Both softwares are available free of charge but ImageJ is more widely compatible. Image editing software must be also purchased if using Image SXM with IS. The facilities and equipment required for inducing and processing sputum are likely to preclude the use of this technique in rural or resource poor settings.
A further limitation of this study is that image capture of macrophages – which can be difficult to differentiate from other cell types (particularly on cytospins stained only with eosin for Image SXM analysis) - was only performed by one reader, with support from a senior cell biologist, without a priori criteria for inclusion. This may have resulted in incorrect identification of some cells. Independent image capture and slide analysis by two individuals with a high level of expertise may improve accuracy of macrophage identification, although this represents an additional challenge for implementing these methods in resource limited settings.
ImageJ method requires higher levels of operator training for image analysis than Image SXM, due to the subjective nature of the analysis process. Further work to assess intra- and inter-observer reliability using the ImageJ method is required before this is widely used – this was not evaluated as part of this study in which only one unblinded reader performed the analysis.
Although previously successfully used with BAL samples, Image SXM appears to not perform as well with IS macrophages. This is possibly due to the heterogenous and granular nature of these macrophages making it difficult for the software to distinguish between cytoplasm and PM, as has been observed in previous studies [
]. We postulate that the difference in appearance compared to BAL macrophages is either due to these being a different population of macrophages, taken from a more proximal part of the airways, or due to cell stress or apoptosis resulting from the IS process, although we did not measure cell viability in this study. Steps were taken to ensure threshold settings were optimised for this batch of images, but due to the heterogeneity seen these settings were not always optimal for each individual image. Image SXM does include an option to adjust the threshold settings manually for different images. This might improve accuracy but would make the process more time-consuming, and would not account for heterogeneity of macrophages within the same image (Fig.
). Optimising the threshold settings for each image might reduce the number of images discarded from Image SXM following visual checking for accuracy (Fig.
). This might increase the sample size and therefore the precision of estimates.
The lack of correlation observed in AMPL results between the two methods is unsurprising given some of the difficulties outlined above. To determine the accuracy of either method, comparison with an external comparator is required, such as an individual’s PM exposure data. This, and assessment of intra- and inter-observer reliability, were beyond the scope of this study. An association between AMPL calculated and the number of peak exposures to PM has been demonstrated in London cyclists [
], but further exploration of this relationship in other settings is required. The results obtained by the ImageJ method in this study are comparable to that of healthy British children (0.41 μm
PM per macrophage) [
]. Other studies using ImageJ methodology have suggested that AMPL does correlate with exposure [
Given the fundamental role of alveolar macrophages in the defence against inhaled pollutants, further exploration of the relationship between AMPL and pathophysiology is an intuitive way to improve understanding of the health impacts of air pollution. Optimising digital analysis software or using alternative methods for quantifying AMPL, such as spectrophotometry, may assist with this, but is unlikely to provide a useful field biomarker of exposure.
Direct measurement of air pollution exposure is costly, logistically complicated and intrusive to the individual. Studies investigating the health impacts of air pollution exposure and the benefits of interventions are limited by the challenges associated with accurately quantifying exposure [
]. A biomarker of air pollution exposure will be a useful tool to facilitate research addressing the high burden of disease associated with air pollution. This small study has not established whether AMPL is an accurate biomarker of pollution exposure, but has compared the feasibility of two previously used methods. The heterogeneity of IS samples complicates digital image analysis methods, and the resource requirements for assessing AMPL from IS are considerable, making it unlikely that this biomarker of exposure will be appropriate for widespread use as a tool for large-scale intervention studies. Priority should be given to developing a point-of-care biomarker of exposure, without the need for specialist training and equipment, to facilitate the large public health intervention trials that are urgently needed. Potential biomarkers requiring further exploration include direct measures of combustion products, such as exhaled carbon monoxide, exhaled carboxyhaemoglobin, exhaled volatile organic compounds or levoglucosan and methoxyphenols in urine [
]. Indirect measures of exposure in sputum, blood and urine, including markers of oxidative stress and endothelial or epithelial damage (such as 8-isoprostane, malondialdehyde, nitric oxide, or surfactant-associated protein D), may also be promising biomarkers [
We are grateful to Dr Steve Barrett, University of Liverpool, who created Image SXM software, for his collaboration during development of this methodology, to Dr Duncan Fullerton, Dr Kondwani Jambo and Dr Khuzwayo Jere for sharing their insights into the use of Image SXM methodology and for their comments on this manuscript. We are also grateful to Professor Jonathon Grigg and Dr Rossa Brugha, Queen Mary, University of London, for sharing their expertise using ImageJ methodology. We are also grateful to the patients and staff of Aintree University Hospital, Liverpool where this work was conducted.
Hannah Jary is a Wellcome Trust funded Clinical PhD Fellow, and the Wellcome Trust provided funding for this study.
The authors declare that they have no competing interests.
HJ, JR, SG and KM designed the study. HJ, LP and KM recruited all participants. HJ obtained and processed all samples, analysed the data, and drafted the manuscript. All authors contributed to and approved the final manuscript.