Significant morphological change in osteoarthritic hips identified over 6-12 months using statistical shape modelling

Area of Science:

• Orthopedics and Sports Medicine
• Radiology and Medical Imaging
• Biomedical Engineering

Background:

• Osteoarthritis (OA) prediction, progression assessment, and treatment response monitoring are critical for developing effective therapies.
• Statistical Shape Modelling (SSM) quantifies geometric variations in the hip joint, offering a comprehensive approach to shape analysis.

Purpose of the Study:

• To evaluate the responsiveness of Statistical Shape Modelling (SSM) in detecting changes in hip shape over a 12-month period.
• To assess SSM's sensitivity in capturing early signs of hip osteoarthritis (OA) progression.

Main Methods:

• Sixty-two participants (mean age 67.1 years) underwent dual-energy X-ray Absorptiometry at baseline, 6, and 12 months.
• Subjects were classified by Kellgren-Lawrence grading (KLG) into control/doubtful (KLG < 1), moderate (KLG = 2), and severe (KLG ≥ 3) OA groups.
• Hip morphology was quantified using SSM, and shape changes were analyzed using generalized estimating equations and standardized response means (SRMs).

Main Results:

• Three SSM modes (1, 3, and 4) correlated with OA severity (KLG0-KLG4).
• SRM magnitudes across the cohort ranged from 0.16 to 0.63.
• The highest SRM (0.91) was observed over 12 months in the moderate OA subgroup (KLG2).

Conclusions:

• Statistical Shape Modelling (SSM) demonstrates sensitivity in capturing hip shape alterations over 6 and 12 months.
• SSM provides a valuable and sensitive quantitative measure for assessing hip osteoarthritis progression.
• This technique aids in monitoring disease progression and evaluating early treatment responses in clinical settings.