Predicting three‐dimensional patellofemoral kinematics from static imaging‐based alignment measures

Abstract

Patellofemoral pain syndrome causes significant discomfort and disability among much of the general population. Despite recent breakthroughs in dynamic three-dimensional imaging technologies to assess pathological patellofemoral motion, such tools remain costly for clinical diagnostics applications. Thus, this study investigated whether three-dimensional patellofemoral kinematics could be predicted from routine two-dimensional static measures of patellofemoral joint alignment quantified from magnetic resonance imaging (MRI) data acquired in full knee extension. Twenty-six volunteers clinically diagnosed with patellofemoral pain (19 F/7 M, 25.9 ± 11.1 years) and 26 control subjects (19 F/7 M, 25.3 ± 7.7 years) were included in this IRB-approved study. Static three-dimensional sagittal T1-weighted gradient recall echo and dynamic MRI scans were acquired. For the dynamic image acquisition, subjects cyclically flexed and extended their knee (at 30 cycles/min) while a full cine-phase contrast MRI set (24 time frames of anatomic images and x-, y-, and z-velocity images) was acquired. From these data, static measures of patellofemoral alignment and three-dimensional patellofemoral kinematics were derived. Single and multiple regressions between static and kinematic variables were evaluated. Although shown reliable, the static MRI measures could only partially predict patellofemoral kinematics, with r(2) -values ranging from 16% to 77%. This makes it imperitave that the current precise, accurate, 3D, dynamic imaging techniques be translated into clinical tools.