Occupational Lung Diseases: Spectrum of Common Imaging Manifestations

Computed Tomography of Contemporary Occupational Lung Disease: A Pictorial Review

Occupational lung disease remains one of the most common work-related illnesses and accounts for most deaths from occupational illness. Occupational lung diseases often have delayed manifestation over decades and nonspecific clinical presentations, making it challenging for clinicians to promptly identify the disease and implement preventive measures. Radiologists play a crucial role in identifying and diagnosing occupational lung diseases, allowing for removal of the exposure and early medical intervention. In this review, we share our clinical and radiologic approach to diagnosing occupational lung disease and its subtypes. A collection of sample cases of occupational lung diseases commonly encountered in the modern era at a large Canadian university hospital is included to facilitate understanding. This review will provide radiologists with valuable insights into recognizing and diagnosing occupational lung diseases.

Respiratory Diseases Associated With Organic Dust Exposure

Organic dusts are complex bioaerosol mixtures comprised of dust and par ticulate matter of organic origin. These include components from bacteria, fungi, pollen, and viruses to fragments of animals and plants commonplace to several environmental/occupational settings encompassing agriculture/farming, grain processing, waste/recycling, textile, cotton, woodworking, bird breeding, and more. Organic dust exposures are linked to development of chronic bronchitis, chronic obstructive pulmonary disease, asthma, asthma-like syndrome, byssinosis, hypersensitivity pneumonitis, and idiopathic pulmonary fibrosis. Risk factors of disease development include cumulative dust exposure, smoking, atopy, timing/duration, and nutritional factors. The immunopathogenesis predominantly involves Toll-like receptor signaling cascade, T-helper 1/T-helper 17 lymphocyte responses, neutrophil influx, and potentiation of manifestations associated with allergy. The true prevalence of airway disease directly attributed to organic dust, especially in a workplace setting, remains challenging. Diagnostic confirmation can be difficult and complicated by hesitancy from workers to seek medical care, driven by fears of potential labor-related consequence. Clinical respiratory and systemic presentations coupled with allergy testing, lung function patterns of obstructive versus restrictive disease, and radiological characteristics are typically utilized to delineate these various organic dust-associated respiratory diseases. Prevention, risk reduction, and management primarily focus on reducing exposure to the offending dust, managing symptoms, and preventing disease progression.

Asbestos exposure diagnosis in pulmonary tissues

The diagnosis of asbestosis requires different criteria depending on whether it is in a clinical or medical/legal setting. In the latter context, only when a "diffuse interstitial fibrosis associated to asbestos bodies (ABs)" is present, it can be said to be asbestosis. Considering the medical/legal setting, the diagnosis must be certain and proven. Unfortunately, it is often difficult to identify ABs by light microscopy (LM), but this does not mean that the diagnosis should be clinically excluded. Other parameters are important, such as working history and/or diagnostic imaging. In addition to LM, normally used for diagnosis, there are other techniques, e.g.: scanning electron microscopy with attached microanalysis microprobe (SEM/EDS), but they require tissue digestion and higher cost. A new approach with micro-Raman spectroscopy and SEM/EDS techniques is able to analyse histological sections without other manipulations that could interfere with analysis of asbestos fibres. In this work, we propose an algorithm for asbestosis diagnosis, especially in the forensic medical field, demonstrating the importance of close collaboration between multiple professionals.

Artificial intelligence in advancing occupational health and safety: an encapsulation of developments

OBJECTIVES

In an era characterized by dynamic technological advancements, the well-being of the workforce remains a cornerstone of progress and sustainability. The evolving industrial landscape in the modern world has had a considerable influence on occupational health and safety (OHS). Ensuring the well-being of workers and creating safe working environments are not only ethical imperatives but also integral to maintaining operational efficiency and productivity. We aim to review the advancements that have taken place with a potential to reshape workplace safety with integration of artificial intelligence (AI)-driven new technologies to prevent occupational diseases and promote safety solutions.

METHODS

The published literature was identified using scientific databases of Embase, PubMed, and Google scholar including a lower time bound of 1974 to capture chronological advances in occupational disease detection and technological solutions employed in industrial set-ups.

RESULTS

AI-driven technologies are revolutionizing how organizations approach health and safety, offering predictive insights, real-time monitoring, and risk mitigation strategies that not only minimize accidents and hazards but also pave the way for a more proactive and responsive approach to safeguarding the workforce.

CONCLUSION

As industries embrace the transformative potential of AI, a new frontier of possibilities emerges for enhancing workplace safety. This synergy between OHS and AI marks a pivotal moment in the quest for safer, healthier, and more sustainable workplaces.

Imaging features and clinical significance of atypical pleural plaques mimicking bone tumors: a retrospective case series

This study aimed to examine the imaging characteristics and clinical implications of atypical pleural lesions that mimic bone tumors and form along the inner margins of consecutive ribs. This retrospective analysis included 45 atypical pleural lesions arising from 13 patients who underwent chest computed tomography (CT) between April 2021 and March 2023. The clinical features, CT findings, and radiologic diagnoses prior to pathologic identification were examined. Pathological findings were reviewed in the surgically resected case. Subgroup analysis was performed based on the presence of concurrent typical pleural plaques. The mean age of the patients was 69.3±8.4 years with a predominance of males (76.9%). The lesions primarily exhibited unilateral involvement (84.6%), being most frequently located in the right mid-level posterior region. Calcification was present in 75.6% of cases, typically seen continuously along the ribs (82.4%). Adjacent rib changes were observed in 28.9% of cases. These lesions were frequently misdiagnosed as osteochondromas or bony spurs (55.6%) by thoracic radiologists. No significant growth was observed during follow-up (n=11, 47±41 months), and the pathological findings were consistent with pleural plaques. Patients with concurrent typical pleural plaques had more atypical pleural lesions without statistical significance (P=0.071) and showed a more even distribution (P=0.039). In conclusion, atypical pleural lesions resembling bone tumors along consecutive ribs represent a distinct subset of pleural plaques. Their unique distribution and morphology should be recognized by radiologists to avoid misinterpretation and unnecessary interventions.