Artificial intelligence has reached such an advanced level of precision that it can now determine a person’s exact age based solely on a chest scan. Developed by scientists in Japan, this remarkable tool was trained using thousands of real radiographs and underwent rigorous testing and fine-tuning. The results demonstrated that the AI system could accurately predict age, with an average deviation of just three years.
To train the AI bot, chest X-rays from 36,000 healthy patients scanned between 2008 and 2021 were gathered from three different sites. The findings, published in The Lancet Healthy Longevity, revealed a strong correlation between the AI’s age estimates and the actual age of the individuals. By analyzing saliency graphs, the researchers discovered distinct patterns in the X-ray scans that corresponded to different age groups. For instance, individuals aged 21 to 40 exhibited colder areas in the lower lung region, while those aged 81 to 100 displayed more red areas around the heart indicating higher temperatures. Moreover, the chest cavity was consistently larger in the younger age group compared to the older age group.
Experts have noted that when the AI system overestimates age, it often indicates the presence of an underlying illness. Scientists from Osaka Metropolitan University consider this breakthrough to be a significant advancement in medical imaging. They believe that the technology could revolutionize disease detection and treatment by enabling early intervention for conditions such as high blood pressure, lung disease, and kidney failure.
In addition to the healthy patients, the researchers also analyzed chest scans from an additional 34,000 individuals with various underlying conditions including asthma, diabetes, and liver disease. The AI’s age estimation aligned with the actual age in these cases as well. Interestingly, when the AI mistakenly estimated a higher age, it was found to be associated with diseases such as chronic obstructive pulmonary disease (COPD) and osteoporosis. These conditions produce noticeable changes in the chest, including the blood vessels, lungs, bones, and heart, which can be detected through X-rays.
The researchers examined saliency maps, which identified the areas on the scan that the AI relied on to determine age. The mediastinum, the region separating the lungs that houses the heart and vital arteries, was of particular interest. This area revealed the accumulation of calcium around the organs, and elevated levels were indicative of disease.
Lead study author Yasuhito Mitsuyama emphasized that their results suggest age estimation based on chest radiography can provide valuable insights into a patient’s overall health status beyond their chronological age. The researchers hope to further develop this research to estimate the severity of chronic diseases, predict life expectancy, and anticipate potential surgical complications.
Overall, the development of AI capable of accurately pinpointing age based on chest scans represents a remarkable advancement in medical technology, with the potential to revolutionize healthcare practices.
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