Semi-automated Alpha Angle Computation Based on ZTE MRI to Quantitatively Evaluate CAM Morphology

Abstract

Introduction: This study developed an open access workflow for semi-automated three dimensional (3D) alpha angle measurement to allow researchers and clinicians to evaluate the 3D degree of cam morphology in a fast and objective manner, regardless of their financial resources.

Method: In the semi-automated workflow geometrical approaches were applied to eight manually segmented 3D models of the proximal femur (four left and four right). These 3D models were created from Zero Echo Time (ZTE) Magnetic Resonance Imaging (MRI) images of four randomly selected individuals from the Feyenoord cohort, thus without radiation exposure. Important landmarks were localized on the 3D models with subsequent radial reformatting and alpha angle computation in 12 radial sections. Novel strategies included radial section-specific spherical least square fitting to approximate the radius of the femoral head, outlier detection to handle surface irregularities and model specific thresholds to account for the asphericity of the femoral head. For six clockwise positions (12:00, 1:00, 2:00, 3:00, 6:00, and 9:00 o’clock), both qualitative and quantitative validation were conducted by comparing the semi-automated
measurements to manual alpha angle measurements performed by an experienced musculoskeletal (MSK) radiologist. To evaluate the inter-observer reliability, the mean absolute difference (MAD) and intra-class correlation (ICC) were calculated for various automatic approaches, depending on which novel strategies were incorporated. Additionally, the radii (mm) and the measurement time (minutes) were compared between the manual and semi-automated approach.

Results: Reliability assessment showed poor agreement with ICCs ranging from -0.02 to 0.40, depending on which automatic approach was used. The highest ICC of 0.40 [95%CI: -0.51 - 0.89] was achieved using a radial section-specific radius without alteration of the spherical threshold or application of outlier detection. MADs ranged from 20°- 23°. Statistically significant differences (p-value <0.003) between manually drawn circular radii and automatically fitted radial section-specific spherical radii were found for 50% of the 3D hip models. All manually drawn circular radii were smaller than the radii of the automated fitted spheres. Variation in radii between and within radial sections were qualitatively and quantitatively demonstrated. Lastly, computation of the 12 clockwise alpha angles was performed by the workflow within 26 seconds, indicating a time difference of approximately 15 minutes compared to manual measurements.

Conclusion: The proposed semi-automated workflow is capable of computing 12 alpha angles across radial sections surrounding the femoral head in a fast and objective manner. The performance of the workflow could be improved by refining landmark localization, enhancing the quality and segmentation of ZTE MRI scans, enlarging the validation dataset and analysis of prior workflow error propagation. This study established that the femoral head is not perfectly spherical. This affects the accuracy of alpha angle measurements as it is strongly sensitive to radius estimation and therefore questions the reliability of the alpha angle as diagnostic measure of cam morphology. Future research should explore the potential of complementary alternative imaging parameters such as the Head-Neck-Offset Ratio (HNOR) and Triangular Index (TI), as well as the use of statistical shape models that incorporate the imperfect spherical morphology of the femoral head.