BACKGROUND: End-stage knee osteoarthritis (OA) commonly results in knee arthroplasty. Three dimensional (3D) supine imaging is often used for pre-operative planning to optimise post-operative knee adduction angles (KAA). However, supine imaging may not represent loaded knee alignment. The aim of this study was to investigate differences in knee alignment under supine, static and dynamic conditions in healthy subjects and subjects with knee OA. METHODS: Nine healthy subjects and 15 subjects with end-stage knee OA were recruited. All subjects underwent supine imaging and motion capture during gait. KAAs were calculated from supine images (SUPINE), upright standing (STATIC) and at the first peak ground reaction force during gait (DYNAMIC), and were compared. RESULTS: KAAs were significantly higher (more varus) during gait compared with static (loaded and unloaded) in healthy subjects (p<0.01) but not in subjects with knee OA. There was a good correlation between SUPINE and DYNAMIC for both healthy and OA subjects (R(2)>0.58), with differences in the two relationships; healthy knees had a higher KAA during gait for any given KAA in the supine position, whereas OA knees that were valgus in imaging became more valgus during gait, and the opposite occurred for varus knees. CONCLUSIONS: Factors that may contribute to the noted differences between healthy and OA subjects include morphological changes in the joint as a result of OA, and gait compensation strategies in people with end-stage OA. Dynamic 3D motion capture provides important information about functional alignment that is not provided by supine imaging or static motion capture. CLINICAL RELEVANCE: Gait analysis may provide useful information to the surgeon during surgical planning of knee arthroplasties.
BACKGROUND: End-stage knee osteoarthritis (OA) commonly results in knee arthroplasty. Three dimensional (3D) supine imaging is often used for pre-operative planning to optimise post-operative knee adduction angles (KAA). However, supine imaging may not represent loaded knee alignment. The aim of this study was to investigate differences in knee alignment under supine, static and dynamic conditions in healthy subjects and subjects with knee OA. METHODS: Nine healthy subjects and 15 subjects with end-stage knee OA were recruited. All subjects underwent supine imaging and motion capture during gait. KAAs were calculated from supine images (SUPINE), upright standing (STATIC) and at the first peak ground reaction force during gait (DYNAMIC), and were compared. RESULTS: KAAs were significantly higher (more varus) during gait compared with static (loaded and unloaded) in healthy subjects (p<0.01) but not in subjects with knee OA. There was a good correlation between SUPINE and DYNAMIC for both healthy and OA subjects (R(2)>0.58), with differences in the two relationships; healthy knees had a higher KAA during gait for any given KAA in the supine position, whereas OA knees that were valgus in imaging became more valgus during gait, and the opposite occurred for varus knees. CONCLUSIONS: Factors that may contribute to the noted differences between healthy and OA subjects include morphological changes in the joint as a result of OA, and gait compensation strategies in people with end-stage OA. Dynamic 3D motion capture provides important information about functional alignment that is not provided by supine imaging or static motion capture. CLINICAL RELEVANCE: Gait analysis may provide useful information to the surgeon during surgical planning of knee arthroplasties.
Authors: Joyce A C van Tunen; Andrea Dell'Isola; Carsten Juhl; Joost Dekker; Martijn Steultjens; Jonas B Thorlund; Hans Lund Journal: BMC Musculoskelet Disord Date: 2018-07-28 Impact factor: 2.362