AI-powered applications are reliable alternative to manual evaluation of pelvic radiographs

Despite advances of three-dimensional imaging pelvic radiographs remain the cornerstone in the evaluation of the hip joint. However, large inter- and intra-rater variabilities were reported due to subjective landmark setting. Artificial intelligence (AI)–powered software applications could improve the reproducibility of pelvic radiograph evaluation by providing standardized measurements.

Schwarz et al conducted a study to evaluate the reliability and agreement of a newly developed AI algorithm for the evaluation of pelvic radiographs.

300 pelvic radiographs from 280 patients with different degrees of acetabular coverage and osteoarthritis (Tönnis Grade 0 to 3) were evaluated. Reliability and agreement between manual measurements and the outputs of the AI software HIPPO (Hip Positioning Assistant 1.03, ImageBiopsy Lab, Vienna, Austria) were assessed for the lateral-center-edge (LCE) angle, neck-shaft angle, sharp angle, acetabular index, as well as the femoral head extrusion index. The algorithm was trained on over 10,000 radiographs from the OAI (Osteoarthritis Initiative study; US six-site multi centre), MOST (Multicenter Osteoarthritis Study, US two site multi-center), CHECK (Cohort Hip and Cohort Knee study; Netherland single center) studies, as well as five sites in Austria.

Key findings of the study were:

• The AI software provided reliable results in 94.3% (283/300).

• The ICC values ranged between 0.73 for the Acetabular Index to 0.80 for the LCE Angle.

• Checking the AI output alone (15.8 ± 4.9 s) was ten times faster than manual measurements (171.0 ± 48.5 s, p < 0.001).

• Agreement between readers and AI outputs, given by the standard error of measurement (SEM), was good for hips with normal coverage (LCE-SEM: 3.4°) and no osteoarthritis (LCE-SEM: 3.3°) and worse for hips with undercoverage (LCE-SEM: 5.2°) or severe osteoarthritis (LCE-SEM: 5.1°).

The authors concluded that – “AI-powered applications are a reliable alternative to manual evaluation of pelvic radiographs. While being accurate for patients with normal acetabular coverage and mild signs of osteoarthritis, it needs improvement in the evaluation of patients with hip dysplasia and severe osteoarthritis.”

Level of Evidence: III, diagnostic study

Further reading:

Can artificial intelligence powered software reliably assess pelvic radiographs? Gilbert M Schwarz, Sebastian Simon et al, International Orthopaedics (2023) 47:945–953 https://doi.org/10.1007/s00264-023-05722-z