Asbestos Fiber Counts Research Articles

The German experience with asbestos-related diseases: a failure of compensation due to the manipulation of science

The world pandemic of asbestos-related diseases results from inadequate prevention and late bans on asbestos use. For years in Germany there has been an annual average of about ten thousand new claims. Many countries deny compensation due to unsound diagnostic applications that have entered into the literature and are used to deny compensation. One such well-established incorrect scientific strategy is the use of quantifying asbestos bodies or fibers in lung tissue and setting restrictive thresholds on the findings in tissues of workers who had been exposed primarily to chrysotile which shows low bio-persistence, movement to the pleura, and rarely forms asbestos bodies. The so called one thousand asbestos body hypothesis for the diagnosis of asbestosis, originating from the German Mesothelioma Register run by the employers’ statutory accident insurance institutions, has been applied in Germany and similarly in several other western countries. As opposed to the well-substantiated hit and run phenomena that has been predominantly applied to chrysotile asbestos, low asbestos body or fiber counts in tissue had been systematically misinterpreted. This, combined with restrictive histopathology definitions, have been used for the manipulation not only of diagnostic criteria but also of science and has had an effect on laws governing compensation. The counting of asbestos bodies or fibers in human lungs should under no circumstances invalidate a qualified occupational history of exposure as the hallmark requisite tool for assessing asbestos exposure and acceptance of asbestos-related diseases in compensation schemes. An outcome suggested by this paper is the need to broaden the WHO beneficial initiative to eliminate ARD worldwide by establishment of an international board of independent scientists on remedial action that would recommend standards for acknowledgement and compensation. Such a board should be supported by national legal branches recognizing possible regional differences and initiating compliance with the recommendations.

Reconstructing historical exposure to asbestos: the validation of 'educated guesses'.

In both the epidemiological and legal context, the causal attribution of asbestos-related lung diseases requires retrospective exposure assessment (REA). To assess the correlation between the retrospective assessment of occupational and anthropogenic environmental exposure to asbestos and its content in the lung tissue. Based on the available exposure information, a team of occupational physicians retrospectively assessed cumulative exposure to asbestos in 24 subjects who died of asbestos-related diseases. The asbestos lung content was analysed using analytical scanning electron microscope (SEM-EDS). The Log10 asbestos fibre count in the autoptic samples was predicted as a function of the Log10 estimated cumulative exposure using univariate regression analysis. The median count of asbestos fibres by grams of dry weight (ff/gdw) in the lung tissue was 81 339 (range 0-2 135 849.06); it was 287 144 (range 0-2 135 849.06) among the occupationally exposed, and 29 671 (range 0-116 891) among the subjects who only had anthropogenic environmental and/or household exposure. Amphiboles, and particularly amosite (52%) and crocidolite (43%), were detected in all the study subjects. Chrysotile was not detected in any of the samples. Overall, the retrospective estimate of lifetime cumulative exposure to asbestos showed a moderate correlation with the total asbestos fibre count in the autoptic lung, with the regression model explaining 38-55% of the total variance. Detailed information on occupational, environmental and household exposure circumstances would be indispensable for experienced industrial hygienists and/or occupational physicians to reliably assess past exposure to amphiboles or mixed types of asbestos.

Asbestos Lung Burden Does Not Predict Survival in Malignant Pleural Mesothelioma: A Necropsy-Based Study of 185 Cases

IntroductionMalignant pleural mesothelioma is an asbestos-related disease with poor survival. The prognostic role of histologic subtype is well established. Some studies (without a biological hypothesis) suggested that higher asbestos lung burden is associated with reduced survival. MethodsWe selected subjects from two series of necropsies: residents in Brescia province (North-West Italy) and workers (or persons living with them) employed in the Monfalcone shipyards (North-East Italy). Asbestos fibers and asbestos bodies in lung samples were counted using a scanning electron and an optical microscope, respectively. Separately in the two series, we analyzed median survival time and fitted multivariable Cox regression models (adjusted for sex, period and age at diagnosis, and histopatholocical diagnosis) to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for three levels of asbestos fiber counts (reference: <1 million fibers/g of dry lung tissue). ResultsWe analyzed 185 necropsies, 83 in Brescia and 102 in Monfalcone. Despite a much higher lung burden in Monfalcone patients, median survival was slightly shorter in Brescia (8.3 mo) than in Monfalcone (10.2 mo). In Brescia, medium (1.0–9.9) and high (10+) fiber burden HRs were 0.91 (95% CI: 0.54–1.53) and 1.23 (95% CI: 0.41–3.70), respectively. In Monfalcone, the corresponding HRs were 1.18 (95% CI: 0.59–2.35) and 1.63 (95% CI: 0.77–3.45), respectively. ConclusionsNo relationship between asbestos lung burden and survival was found. Histologic subtype was the strongest prognostic determinant.

Round-Robin Tests with Relocatable Coverslips Improve Asbestos Fibre Counting.

Asbestos fibre counting by phase-contrast microscope is subject to many sources of variation, including those dependent on the analyst. In this study, asbestos sample slides prepared with relocatable coverslips have been used for fibre counting among voluntary analysts to evaluate their proficiency. One slide of amosite and one of chrysotile were distributed to all the analysts, and three proficiency testing rounds were conducted for amosite and four for chrysotile. Each relocatable coverslip has a report in which are reported for each viewing field both the number of certified fibres (Verified Fibres) and a drawing representing the shape and position of the individual fibres. In the first round, the analysts were asked to report only the number of fibres counted in each of the predesignated fields of view. In the other rounds, subsequently developed, the analysts had to report the number and the position of the fibres for each field. The reported number of fibres and their position in each of the designed fields were evaluated against their respective verified fibres, to identify types of error. Discrepancies between reported fibres and verified fibres in each field of view have been used to evaluate the proficiency of the analysts. The discrepancies can be positive (D+) or negative (D-) depending on whether the analyst counts, for a specific field of view, more or less fibres compared to the verified fibres. The score is calculated using the following equation: Score = (1 - ∑D+ + ∑│D-│/VF) × 100. An analyst obtaining a score of ≥60, which corresponds to (∑D+ + ∑│D-│)/VF ≤ 0.40, is proficient. The number of laboratories that participating in this study varied from 13 to 17 depending on the rounds. For amosite fibre counts, the results were generally good compared to a proficiency score of 60. The major error made by analysts was the counting of fibres shorter than 5 µm, where this error was of 62% of extra fibres and accounted for 8% over-estimation of amosite fibres. For chrysotile, a score of ≥50 has been used to consider an analyst as proficient. The results of chrysotile fibres showed that in the first round all analysts counted less than fifty per cent of the verified fibres. In the second round 10 analysts out of 13 reached a score of ≥50, 8 of 16 in the third and 10 of 12 in the fourth. For chrysotile fibres, the error relating to the counting of fibres shorter than 5 µm was of 56% of extra fibres, but the error that most influenced the results was the number of oversight-missing fibres. This type of error accounted for 97% of the missing fibres and for the 29% under-estimation of the chrysotile fibres. For amosite fibre counting, results of this study show an improvement of the analyst's performance. For the chrysotile fibre count, although there is a significant improvement in the comparison between some rounds, this is not continuous over time.

Detection and comparison of fiber count concentration in processing environment of asbestos and man-made mineral fiber

Objective: To connect with the measurement data of asbestos dust fiber concentration in foreign countries, improve the accuracy of asbestos fiber detection in China, and understand the dust exposure in the working environment of asbestos and man-made mineral fiber production and processing sites in Zhejiang Province. The fiber count concentrations of working environment in glass fiber, ceramic fiber and asbestos processing plants were measured and compared. Methods: The dust concentration in the working environment of two glass fiber factories, one ceramic fiber factory and eight asbestos products processing factories was measured. The total dust mass concentration was measured according to GBZ/T 192.1-2007, and the fiber count concentration was measured by phase contrast microscope. Kruskal Wallis was used to test and compare the dust concentration in the working environment of each post. The correlation between asbestos mass concentration and fiber count concentration was analyzed by Spearman correlation. Results: Under the phase contrast microscope, there were many short and fine asbestos fibers in the field of vision, and there were many impurities around. The average dust concentration of asbestos processing plant was 3.2 f/ml, and the dust concentration of cotton ginning was the highest (6.68 f/ml) . There was a significantly positive correlation between asbestos fiber count concentration and mass concentration (r=0.535, P=0.033) . The average fiber count concentration of glass fiber factory was 0.001 f/ml, and the highest was 0.005 f/ml. The average fiber count concentration of ceramic fiber factory was 0.001 f/ml, and the highest was 0.006 f/ml. Conclusion: The fiber count concentration in the working environment of asbestos factory in Zhejiang Province is obviously over the standard, which is one of the important reasons for the high incidence of mesothelioma in this area. Short and small asbestos fibers are easy to be ignored when counting. It is necessary to improve the actual operation process of fiber counting to form a laboratory standard in China.

Asbestos Fibre and Mineral Counts from Filtered Dust Collected in Human Settlements Asbestos Mine Dumps in Mpumalanga Province, Republic of South Africa

Dust generation sources come from mining sites including mine dumps, crushing, hauling, grinding and offloading of waste material from open pit and underground operation and non-operations, movement of trucks on unpaved roads, etc. Many mine dumps in South Africa are not rehabilitated due to the possibility of re-mining in the case of asbestos dumps or have been abandoned by previous owners for different reasons. Some of the reasons for abandonment include bankruptcy, ineffective enforcement, lack of financial assurance, minimal penalties for non-compliance and commodities like gold, asbestos and coal are affected. Historically, only long asbestos fibres were used for manufacturing purpose. While short fibres were unwanted

CDKN2A copy number and p16 expression in malignant pleural mesothelioma in relation to asbestos exposure

BackgroundDeletion of the CDKN2A locus is centrally involved in the development of several malignancies. In malignant pleural mesothelioma (MPM), it is one of the most frequently reported genomic alteration. MPM is strongly associated with a patients’ asbestos exposure. However, the status of CDKN2A and the expression of the corresponding protein, p16, in relation to MPM patient’s asbestos exposure is poorly known. Copy number alterations in 2p16, 9q33.1 and 19p13 have earlier been shown to accumulate in lung cancer in relation to asbestos exposure but their status in MPM is unclear.MethodsWe studied DNA copy numbers for CDKN2A using fluorescence in situ hybridization (FISH) and p16 expression by immunohistochemistry (IHC) in 92 MPM patients, 75 of which with known asbestos exposure status. We also studied, in MPM, copy number alterations in 2p16, 9q33.1 and 19p13 by FISH.ResultsWe were unable to detect an association between p16 expression and pulmonary asbestos fiber count in MPM tumor cells. However, significantly more MPM patients with high pulmonary asbestos fiber count (> 1 million fibers per gram [f/g]) had stromal p16 immunoreactivity than MPM of patients with low exposure (≤ 0.5 million f/g) (51.4% vs 16.7%; p = 0.035, Chi-Square). We found that an abnormal copy number of CDKN2A in MPM tumor cells associated with a high pulmonary asbestos fiber count (p = 0.044, Fisher’s Exact test, two-tailed). In contrast to our earlier findings in asbestos associated lung cancer, DNA copy number changes in 2p16, 9q33 and 19p13 were not frequent in MPM although single cases with variable copy numbers on those regions were seen.ConclusionsWe found two instances where the gene locus CDKN2A or its corresponding protein expression, is associated with high asbestos exposure levels. This suggests that there may be biological differences between the mesotheliomas with high pulmonary asbestos fiber count and those with low fiber count.

Abstract 3441: Genome-wide gene expression analysis in asbestos-related non-small cell lung cancer

Abstract Recently we examined genome-wide DNA methylation in lung cancer from patients occupationally exposed to asbestos (Kettunen et al 2017 Int J Cancer). Distinct methylation changes in lung tumors were shown in relation to asbestos exposure and tobacco smoking. Now we have performed genome-wide gene expression microarray experiments with Agilent SurePrint G3 Human GE 8x60K v3 Microarrays using same samples. Patients had been interviewed for work and smoking histories and their pulmonary asbestos fiber counts were measured by electron microscopy. Fresh-frozen lung cancer tissues (LC, n=42) and paired microscopically normal peripheral lung tissues (NT, n=21) were studied. After data processing and analyses for differential gene expression, data were filtered for adjusted p &amp;lt; 0.05 and fold change &amp;gt; 1.5. Principal component analysis showed distinct clusters of normal lung and cancer tissues. In lung cancers compared with their paired microscopically normal lung, 5931 genes such as those involved in neutrophil degranulation and immune system were differentially expressed, with the lowest adjusted p=6.71E-37. In our preliminary analyses, 34 genes in NT and 44 in LC, and 152 genes in NT and 12 in LC showed differential expression when the asbestos-exposed were compared to non-exposed and current smokers to ex-smokers, respectively. The genes differentially expressed in relation to smoking or to asbestos exposure had the lowest adjusted p=8.50E-06 and 9.83E-04, respectively. Within differential gene expression related to asbestos exposure, chemokine activity and regulation of cellular protein metabolic processes were implicated whereas microtubules and positive regulation of transcription were related with tobacco smoking burden. In conclusion, comparison of gene expression patterns between lung cancer tissue and paired normal lung showed distinct principal component analysis clusters. Our preliminary data suggest different major biological processes in gene expression for these exposures. Financial support from the Cancer Society of Finland (2014 and 2015) is gratefully acknowledged. Citation Format: Eeva Kettunen, Veer Singh Marwah, Henrik Wolff, Dario Greco, Kirsti Husgafvel-Pursiainen. Genome-wide gene expression analysis in asbestos-related non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3441.

Malignant mesothelioma diagnosed at a younger age is associated with heavier asbestos exposure.

Asbestos exposure is the main etiology of malignant mesothelioma, but there are conflicting data on whether the intensity of exposure modulates the development of this disease. This study considered 594 patients with malignant mesothelioma for whom count data on asbestos bodies and fibers (per gram of wet lung tissue) were available. The relationships between age at diagnosis (a time-to-event outcome variable) and these two measures of internal asbestos exposure, along with other possible modulating factors (sex, tumor location, histological subtype and childhood exposure), were assessed on multivariable Cox proportional hazard models, stratifying by decade of birth year. For both measures of asbestos in lung tissue, younger age at diagnosis was associated with higher internal measures of exposure to asbestos. Stratified Cox analyses showed that for each doubling in asbestos body count patients were 1.07 times more likely to be diagnosed at a younger age [hazard ratio (HR) = 1.07; 95% confidence interval (CI), 1.04-1.09; P = 2.2 × 10-7] and for each doubling in asbestos fiber count patients were 1.13 times more likely to be diagnosed at a younger age (HR = 1.13; 95% CI, 1.09-1.17; P = 8.6 × 10-11). None of the other variables considered were associated with age at diagnosis. Our finding that tumors become clinically apparent at a younger age in heavily exposed subjects suggests that asbestos is involved not only in the malignant mesothelioma tumor initiation but, somehow, also in the progression of the disease.

Joint Iranian-Russian studies of airborne asbestos concentrations in Tehran, Iran, in 2017

Assessment of airborne asbestos in urban areas of Tehran is important due to its potential health risks posed by a significant excess of current standards. Determination of airborne fibers can be performed using Phase Contrast Microscopy (PCM) as well as such a modern technique as Facade pane and its spectrum (SEM). Since PCM cannot differentiate asbestos and non-asbestos fibers, SEM is recommended to monitor the airborne asbestos content. The objective of this study was to determine asbestos fiber concentrations in ambient air in different areas of Tehran. Following the collection of samples using standard methods, we determined all fiber counts using PCM and asbestos fiber counts using SEM with X-ray diffraction microanalysis. The study results were then compared to the data related to the past six years obtained from the Air Quality Control Company (Iran) conducting annual airborne dust measurements in residential areas of Tehran using PCM. It should be noted that the scope of activities of the Air Quality Control Company did not include differentiation of asbestos from non-asbestos fibers.According to the results, all airborne fibrous particles sampled were either organic or mineral fibers, the appearance and specter of which were different from those of asbestos. Filter loading with mineral and organic fibers as well as soot particles from automobile exhausts indicated generally high ambient air pollution at all sampling sites. Optical and electron microscopy analyses of five dust samples collected from horizontal outdoor surfaces detected no asbestos fibers. We recommend regular monitoring of ambient air pollution in the streets of Tehran at different seasons of the year and establishing asbestos fiber concentrations using scanning electron microscopy for complete characterization of air pollution.

Calibration confidence regions for asbestos fibers with heteroscedasticity and interlaboratory variability

It is well known that asbestos exposure causes mesothelioma and asbestosis. We present statistical methodologies for analyzing airborne asbestos fiber counts measured by transmission electron microscopy. We observed from multiple laboratories that the variability of asbestos measurements increases with the true concentration levels. In order to account for the heteroscedasticity and between-laboratories variation of asbestos fiber counts, we use a two-component mixed model as well as a gamma mixed model. We construct calibration confidence regions for unknown true measurements borrowing strength from multiple laboratories. The performances of our calibration confidence regions and their robustness are studied via simulation. To illustrate our results, we analyze a real data set of amosite asbestos.

Confidence Intervals for Asbestos Fiber Counts: Approximate Negative Binomial Distribution.

The negative binomial distribution is adopted for analyzing asbestos fiber counts so as to account for both the sampling errors in capturing only a finite number of fibers and the inevitable human variation in identifying and counting sampled fibers. A simple approximation to this distribution is developed for the derivation of quantiles and approximate confidence limits. The success of the approximation depends critically on the use of Stirling's expansion to sufficient order, on exact normalization of the approximating distribution, on reasonable perturbation of quantities from the normal distribution, and on accurately approximating sums by inverse-trapezoidal integration. Accuracy of the approximation developed is checked through simulation and also by comparison to traditional approximate confidence intervals in the specific case that the negative binomial distribution approaches the Poisson distribution. The resulting statistics are shown to relate directly to early research into the accuracy of asbestos sampling and analysis. Uncertainty in estimating mean asbestos fiber concentrations given only a single count is derived. Decision limits (limits of detection) and detection limits are considered for controlling false-positive and false-negative detection assertions and are compared to traditional limits computed assuming normal distributions.

Differential Counting of Asbestos Using Phase Contrast and Fluorescence Microscopy.

Considering the increasing use of various asbestos substitutes, asbestos risk management in many industries may require accurate techniques for detecting and distinguishing asbestos from non-asbestos fibers. Using fluorescently labeled asbestos-binding proteins, we previously developed a novel method for detection and counting of asbestos fibers under fluorescence microscopy (FM). This method can provide speedy, on-site detection and identification of the asbestos fibers and has higher sensitivity than phase contrast microscopy (PCM). However, current asbestos exposure limits are derived from risk assessments based on epidemiological studies that were conducted using PCM fiber counts. Therefore, the sensitivity of asbestos testing should be maintained at PCM level to properly assess compliance with these limit values. Here, we developed and tested a novel application of FM as a differential counting method that complements PCM analysis and is fully compatible with the PCM-based epidemiological data. In the combined PCM-FM method, the fluorescent asbestos-binding probe is applied prior to filter clearing. The method makes it possible to easily switch between two microscopic techniques while analyzing the same fields of view: PCM is used for counting fibers, and FM for differentiating asbestos from non-asbestos fibers. Using airborne dust samples from demolition sites in Japan, we compared PCM-FM with scanning electron microscopy (SEM)-based differential counting method. Statistical analysis indicated a slight conservative bias of PCM-FM method, combined with relatively high variability across the full range of fiber concentrations in our sample set. Using correlative microscopy, we also evaluated the specificity of FM staining, which is a potential cause of variability between the two methods. The energy-dispersive X-ray analysis indicated that ~95% of fluorescently stained fibers in the demolition site samples were correctly identified as asbestos. While further research is needed to fully clarify the causes of variability between FM- and SEM-based differential counting, PCM-FM could be used for rapid and selective detection of asbestos fibers in field samples.

Abstract 2765: Asbestos exposure-related DNA methylation markers: a validation study in non-small cell lung tumors

Abstract Introduction. We have earlier explored the epigenome-wide DNA methylation in lung tumors. The study subjects, mostly smokers, consisted of lung cancer patients highly exposed to asbestos and those without exposure. We found methylation markers that associated either with sample type or exposure (asbestos or tobacco smoke) (Kettunen et al submitted). In this validation study, we focused on estimating the prevalence of the distinct methylation markers in a larger material of lung tumor patients with detailed exposure data available. Study design, subjects, and methods. We investigated the DNA methylation of selected markers in a validation set of 69 non-small cell lung cancer cases, tumor (T) and normal lung (N) from each. The patients, given a written informed consent, had been interviewed for detailed data on work and smoking history (as tobacco smoking pack-years, PY), and the pulmonary asbestos fiber counts quantified. Smoking-related methylation was studied in lung cancer groups of heavy-smokers (PYs higher than 36) vs lighter-smokers (PYs 36 or less) whereas methylation in asbestos-exposed lung tumor patients were compared with that in non-exposed lung tumor patients. DNA methylation was studied in tumor (T) and matched peripheral normal (N) lung tissue using pyrosequencing. Results. Numerous CpG positions in T vs N and eleven sites in asbestos-exposed tumors had indicated significant methylation variation (MVPs). Twenty-six differentially methylated positions (DMPs) having mean delta beta of at least 10% had been revealed in T vs N. Tobacco smoking- and asbestos exposure-related methylation sites were distinct, involving different CpG sites. We chose to validate five MVPs and four DMPs, both hypo- and hypermethylated CpG sites that were investigated using two instrumentation PSQ96MA and Pyromark Q24. The validation study set indicated good performance in pyrosequencing and we could demonstrate methylation of selected sites in relation to malignancy and exposure in this larger material. Conclusions. The central observations of the methylation showing distinct changes in relation to sample types and patients’ exposure status could be validated in a larger material. Significant methylation variation was observed in lung tumors. Citation Format: Eeva Kettunen, Kristina Stuopelytė, Hector Hernandez-Vargas, Henrik Wolff, Sisko L. Anttila, Zdenko Herceg, Sonata Jarmalaite, Kirsti Husgafvel-Pursiainen. Asbestos exposure-related DNA methylation markers: a validation study in non-small cell lung tumors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2765.

Comments on the 2014 Helsinki Consensus Report on Asbestos

BackgroundThe Finnish Institute of Occupational Health (FIOH) convened an Expert Committee in 2014 to update the 1997 and 2000 Helsinki criteria on asbestos, asbestosis, and cancer. MethodsThe Collegium Ramazzini reviewed the criteria for pathological diagnosis of the diseases caused by asbestos presented in the 2014 Helsinki Consensus Report and compared them with the widely used diagnostic criteria developed in 1982 by the College of American Pathologists and the National Institutes of Occupational Safety and Health (CAP-NIOSH). FindingsThe sections of the Helsinki Consensus Report dealing with pathological diagnosis are based on a biased and selective reading of the scientific literature. They are heavily influenced by the outdated and incorrect concept that analysis of lung tissue for asbestos bodies and asbestos fibers can provide accurate information on past exposure to asbestos. Five specific problems are : 1.Over-reliance on the detection of “asbestos bodies” as indicators of past exposure to asbestos.2.Over-reliance on asbestos fiber counts in lung tissue as an indicator of past exposure to asbestos.3.Use of the scanning electron microscope (SEM) at low magnification as a tool for evaluation of asbestos-related disease.4.Failure to recognize that chrysotile is the predominant type of asbestos fiber found in pleural mesothelioma tissue.5.Postulating the existence of a threshold for development of an asbestos-related lung cancer. ConclusionAccurate diagnosis of the diseases caused by asbestos must be based on a carefully obtained history of occupational exposure. An accurate exposure history is a far more sensitive and specific indicator of asbestos exposure than asbestos body counting or lung fiber burden analysis. Ethical noteThe sections of the 2014 Helsinki Consensus Report on asbestos, asbestosis, and cancer dealing with pathologic diagnosis of the diseases caused by asbestos appear to have been influenced by members of the Expert Committee with undisclosed financial conflicts of interest.

Collegium Ramazzini: Comments on the 2014 Helsinki consensus report on asbestos.

Collegium Ramazzini: Comments on the 2014 Helsinki consensus report on asbestos.

Development of an automated asbestos counting software based on fluorescence microscopy.

An emerging alternative to the commonly used analytical methods for asbestos analysis is fluorescence microscopy (FM), which relies on highly specific asbestos-binding probes to distinguish asbestos from interfering non-asbestos fibers. However, all types of microscopic asbestos analysis require laborious examination of large number of fields of view and are prone to subjective errors and large variability between asbestos counts by different analysts and laboratories. A possible solution to these problems is automated counting of asbestos fibers by image analysis software, which would lower the cost and increase the reliability of asbestos testing. This study seeks to develop a fiber recognition and counting software for FM-based asbestos analysis. We discuss the main features of the developed software and the results of its testing. Software testing showed good correlation between automated and manual counts for the samples with medium and high fiber concentrations. At low fiber concentrations, the automated counts were less accurate, leading us to implement correction mode for automated counts. While the full automation of asbestos analysis would require further improvements in accuracy of fiber identification, the developed software could already assist professional asbestos analysts and record detailed fiber dimensions for the use in epidemiological research.

The analysis of asbestos count data with “nondetects”: The example of asbestos fiber concentrations in the lungs of brake workers

In the analysis of tissue for asbestos fibers, some measurements may be below the analytical detection limit (nondetects). The use of maximum likelihood and survival analysis methods have been recommended to perform comparisons between subjects in the presence of nondetects. When the data consist of "counts" another method is useful. This method is discussed, and illustrated with an analysis of asbestos lung burden data among brake mechanics previously analyzed by other methods. Statistical models for count data, namely Poisson and negative binomial regression, were used to compare the asbestos fiber concentrations in the lungs of brake mechanics with those of control subjects. The fit of the models was assessed with an analysis of residuals. The negative binomial regression models fit the data well. The concentrations of Quebec asbestos fibers in the lungs of the brake mechanics were significantly higher than in the control population. Helsel recommended the use of maximum likelihood and survival analysis methods to perform comparisons in the presence of nondetects. When analyzing asbestos fiber count data, or other count data arising in occupational or environmental health, the use of models such as the Poisson and negative binomial may be added to the analyst's toolbox. Benefits are that neither of these methods requires the substitution of arbitrary values for the nondetects and that programs for the computation of count data models are contained in popular statistical software packages.

Accumulation of genomic alterations in 2p16, 9q33.1 and 19p13 in lung tumours of asbestos-exposed patients

We have previously demonstrated an association between genomic alterations in 19p13, 2p16, and 9q33.1 and asbestos exposure in patients' lung tumours. This study detected allelic imbalance (AI) in these regions in asbestos-exposed lung cancer (LC) patients' histologically normal pulmonary epithelium. We extended the analyses of tumour tissue to cover a large LC patient cohort and studied DNA copy number alteration (CNA) and AI in 19p13, 2p16, and 9q33.1 for the first time in combination. We found both CNA and AI in ≥2/3 of the regions to be significantly and dose-dependently (P < 0.001) associated with pulmonary asbestos fibre count. Twenty percent of the exposed patients' LC showed CNA in ≥2/3 of the regions, whereas none of the non-exposed patients' LC showed CNA in more than one region. AI was evident in 89% of the exposed and in only 26% of the non-exposed patients' LC. The genomic alterations in 19p13, 2p16, and 9q33.1 in compilation identified asbestos-exposed patients' lung tumours better than each of the regions alone. These alterations form the basis for the development of a combinatorial molecular assay that could be used to identify asbestos-related LC.

Airborne asbestos fibres and mesothelioma in the last 20 years in Egypt: a review

Asbestos has been used in Egypt ever since 2000 – 3000 BC for embalming the bodies of Egyptian pharaohs. Little data is available on airborne asbestos fibre counts in the occupational and environmental settings. Counts ranged between 0.0 – 2.7 f/cc and 0.007 – 3.0 f/cc inside and outside various industrial workplace sites, respectively at Sigwart (El–Maasara and Shoubra El–Kheima) companies in Cairo. Asbestos counts ranged between 0.0244 – 0.1389 f/cc in the surrounding areas of the ORA–Egypt company in the 10th of Ramadan City, which has been shut down since 2004. Malignant pleural mesothelioma (MPM) is becoming an increasing problem in Egypt. MPM is related to the inhalation of asbestos fibres in low counts and is incurable when diagnosed. According to official registry data, most MPM cases were living close to asbestos production companies. Mesothelioma incidence was analyzed and studied in the available data during the period 1984–2005. Mesothelioma incidences increased from 159 cases during 1984 – 1999 to 733 cases during 2000 – 2005. The age of the patients ranged between 17 to 90 years with a mean age of 54 years. The survival age varied between 6 to 15 months with median survival was approximately 1 year from diagnosis. Females represented ~39 % of the cases and males represented ~60% with male to female ratio of ~1.7.