Do You Need a DEXA Scan? DEXA scans measure your bone density, lean muscle, and adipose visceral tissue. But unless you're an athlete or approaching menopause, you probably don't need a detailed full-body scan. All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links.

Osteoporosis and fragility fractures have emerged as major public health concerns in an aging population. However, measuring age-related changes in bone density using dual-energy X-ray absorptiometry has limited personalized risk assessment due to susceptibility to interference from various factors. In this study, we propose an innovative statistical model of bone pixel distribution in fine-segmented computed tomography (CT) images, along with a novel approach to measuring bone density based on CT values of bone pixels. Our findings indicate that bone density exhibits a linear decline with age during adulthood between the ages of 39 and 80, with the rate of decline being approximately 1.6 times faster in women than in men. This contradicts the widely accepted notion that bone density starts declining in women at menopause and in men at around 50 years of age. The linearity of age-related changes provides further insights into the dynamics of the aging human body. Consequently, our findings suggest that the definition of osteoporosis by the World Health Organization should be revised to the standard deviation of age-based bone density. Furthermore, these results open up new avenues for research in bone health care and clinical investigation of osteoporosis.

Artificial intelligence (AI) is used in a wide variety of health care settings, from analyzing medical images to assisting with surgical procedures. While AI can sometimes outperform trained clinicians, these superhuman abilities are not always fully understood. In a recent study published in The Lancet Digital Health, researchers found that AI models could accurately predict self-reported race in several different types of radiographic images--a task not possible for human experts. These findings suggest that race information could be unknowingly incorporated into image analysis models, which could potentially exacerbate racial disparities in the medical setting. "AI has immense potential to revolutionize the diagnosis, treatment, and monitoring of numerous diseases and conditions and could dramatically shape the way that we approach health care," said first study author and NIBIB Data and Technology Advancement (DATA) National Service Scholar Judy Gichoya, M.D. "However, for AI to truly benefit all patients, we need a better understanding of how these algorithms make their decisions to prevent unintended biases."

Diagnosing emphysema and classifying its severity have long been more art than science. "Everybody has a different trigger threshold for what they would call normal and what they would call disease," said U. Joseph Schoepf, M.D., director of cardiovascular imaging for MUSC Health and assistant dean for clinical research in the Medical University of South Carolina College of Medicine. And until recently, scans of damaged lungs have been a moot point, he said. "In the past, if you lost lung tissue, that was it. The lung tissue was gone, and there was very little you could do in terms of therapy to help patients," he said.

Diagnosing emphysema and classifying its severity have long been more art than science. "Everybody has a different trigger threshold for what they would call normal and what they would call disease," said U. Joseph Schoepf, M.D., director of cardiovascular imaging for MUSC Health and assistant dean for clinical research in the Medical University of South Carolina College of Medicine. And until recently, scans of damaged lungs have been a moot point, he said. In the past, if you lost lung tissue, that was it. The lung tissue was gone, and there was very little you could do in terms of therapy to help patients.

"Everybody has a different trigger threshold for what they would call normal and what they would call disease," said U. Joseph Schoepf, M.D., director of cardiovascular imaging for MUSC Health and assistant dean for clinical research in the Medical University of South Carolina College of Medicine. And until recently, scans of damaged lungs have been a moot point, he said. "In the past, if you lost lung tissue, that was it. The lung tissue was gone, and there was very little you could do in terms of therapy to help patients," he said. But with advancements in treatment in recent years has come an increased interest in objectively classifying the disease, Schoepf said.