New AI-powered method detects elusive facet syndrome in lower back pain

Scientists at Perm National Research Polytechnic University (PNRPU) have created a new way to diagnose lower back pain. The method focuses on facet syndrome, a condition that is often hard to detect with standard imaging techniques. Researchers say it could help doctors identify problems earlier and more accurately than before. Facet syndrome causes pain when small joints in the spine become misaligned or inflamed. Standard CT scans struggle to show the joint capsule clearly, making diagnosis difficult. The PNRPU team developed a solution by analysing the geometry of joints, vertebrae, and discs.

A virtual model of a spinal motion segment was built to study how stress affects the joint capsule. This model helps predict when capsule deformation might lead to subluxation—a partial dislocation of the joint. By using clinical data, the researchers established numerical ranges to distinguish between normal and pathological conditions. The new method also calculates a personalised strength threshold for each patient. This threshold indicates the point at which the joint capsule may deform enough to cause pain. Doctors can now use these findings to assess patients more precisely and start treatment sooner.

The breakthrough offers a clearer way to diagnose facet syndrome, a common but elusive cause of lower back pain. With earlier detection, patients may receive treatment before their condition worsens. The model’s ability to personalise thresholds could also improve how doctors manage individual cases.