Radiological Imaging Indicators of Survival in Trachea and Lung Cancers: A Global Perspective
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Background Respiratory system cancer has long been a global health issue, with tracheal, bronchial, and lung cancers ranking second in incidence and first in mortality worldwide. This study aims to analyse recent data to understand the global burden, trends, and risk factors for respiratory system cancer, facilitating Improved prevention and treatment strategies. Methods We conducted a study on respiratory system cancer using data from the Global Cancer Observatory and the Cancer Incidence in Five Continents databases. We collected information on the incidence of cancers, risk factors, the final estimates of incidence and mortality rates were multiplied with population data from the United Nations Development Program. The age standardized rates were generated by GLOBOCAN using the world standard population. Results with 2,481,000 cases and 1,817,000 related deaths, trachea and lung cancer had the highest incidence. Asia had the highest incidence and mortality rates of cancer in 2023, with 1,566,000 new cases and 1,142,000 deaths. According to UN regions, Eastern Asia had the highest age-standardized incidence and mortality rates (per 100,000 people) in 2022, at 39.4 and 25.1, respectively. However, there were notable regional differences in the cancer burden, with the lowest rates observed in Western Africa (2.1 and 2.0), Middle Africa (1.3 and 2.2), and Eastern Africa (3.2 and 3.0). In crude incidence and mortality rates Eastern Asia had the highest rates, with 76.9 incidence and 52.7 mortality while the lowest crude rates occurring in Eastern Africa (1.6 and 1.5), Middle Africa (1.0 and 1.0), and Western Africa (1.0 and 0.9). China reported 1,610,000 incidence cases and 733,000 deaths from trachea and lung cancer in 2022, the most of any country. Conclusion In summary, this study supports the role of lung lesions as useful imaging biomarkers by highlighting their prognostic significance in lung disease. The results emphasize that in order to enhance patient outcomes, clinical workflows must integrate cutting-edge imaging methods and AI-driven analysis.