Russian Researchers Develop a Program to Predict the Risk of Spinal Disorders
Russian scientists have developed a predictive program capable of identifying spinal disease risks 10–15 years before severe injuries occur, opening new opportunities for early intervention and personalized preventive medicine.
A New AI-Enhanced Tool for Early Diagnosis
Scientists from Perm National Research Polytechnic University and Perm State Medical University named after Academician Wagner have patented a software system designed to detect early age‑related spinal changes. The algorithm is rooted in a multi‑year study of how the human axial skeleton transforms over a lifetime.
Researchers examined the thoracic spine of men and women across various age groups using CT imaging. For three key vertebrae, they measured height, width, anteroposterior dimensions, and radiographic density. With age, vertebrae gradually lose height and widen, causing the spine to deviate from its natural anatomical structure. As load distribution shifts, discs deteriorate more rapidly, leading to chronic pain, fatigue during walking, shrinking bone strength, and a higher risk of fractures. These changes often manifest externally as stooping and reduced height — conditions that motivated radiologists to create this early‑diagnostic tool.
Predicting and Preventing Long-Term Damage
At the center of the program is a mathematical model describing regularities in age‑related skeletal changes.
The system compares patient indicators with age‑specific norms and detects deviations. Unlike traditional diagnostic approaches that reveal structural defects only after they form, this CT‑analysis program can identify risks 10–15 years before major injuries occur, enabling timely preventive care.
