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Which Two-dimensional Radiographic Measurements of Cam Femoroacetabular Impingement Best Describe the Three-dimensional Shape of the Proximal Femur?

Atkins, Penny R., BS; Shin, YoungJae; Agrawal, Praful, MS; Elhabian, Shireen Y., PhD; Whitaker, Ross T., PhD; Weiss, Jeffrey A., PhD; Aoki, Stephen K., MD; Peters, Christopher L., MD; Anderson, Andrew E., PhD

Clinical Orthopaedics and Related Research®: January 2019 - Volume 477 - Issue 1 - p 242–253
doi: 10.1097/CORR.0000000000000462
BASIC RESEARCH
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Background Many two-dimensional (2-D) radiographic views are used to help diagnose cam femoroacetabular impingement (FAI), but there is little consensus as to which view or combination of views is most effective at visualizing the magnitude and extent of the cam lesion (ie, severity). Previous studies have used a single image from a sequence of CT or MR images to serve as a reference standard with which to evaluate the ability of 2-D radiographic views and associated measurements to describe the severity of the cam lesion. However, single images from CT or MRI data may fail to capture the apex of the cam lesion. Thus, it may be more appropriate to use measurements of three-dimensional (3-D) surface reconstructions from CT or MRI data to serve as an anatomic reference standard when evaluating radiographic views and associated measurements used in the diagnosis of cam FAI.

Questions/purposes The purpose of this study was to use digitally reconstructed radiographs and 3-D statistical shape modeling to (1) determine the correlation between 2-D radiographic measurements of cam FAI and 3-D metrics of proximal femoral shape; and 2) identify the combination of radiographic measurements from plain film projections that were most effective at predicting the 3-D shape of the proximal femur.

Methods This study leveraged previously acquired CT images of the femur from a convenience sample of 37 patients (34 males; mean age, 27 years, range, 16-47 years; mean body mass index [BMI], 24.6 kg/m2, range, 19.0-30.2 kg/m2) diagnosed with cam FAI imaged between February 2005 and January 2016. Patients were diagnosed with cam FAI based on a culmination of clinical examinations, history of hip pain, and imaging findings. The control group consisted of 59 morphologically normal control participants (36 males; mean age, 29 years, range, 15-55 years; mean BMI, 24.4 kg/m2, range, 16.3-38.6 kg/m2) imaged between April 2008 and September 2014. Of these controls, 30 were cadaveric femurs and 29 were living participants. All controls were screened for evidence of femoral deformities using radiographs. In addition, living control participants had no history of hip pain or previous surgery to the hip or lower limbs. CT images were acquired for each participant and the surface of the proximal femur was segmented and reconstructed. Surfaces were input to our statistical shape modeling pipeline, which objectively calculated 3-D shape scores that described the overall shape of the entire proximal femur and of the region of the femur where the cam lesion is typically located. Digital reconstructions for eight plain film views (AP, Meyer lateral, 45° Dunn, modified 45° Dunn, frog-leg lateral, Espié frog-leg, 90° Dunn, and cross-table lateral) were generated from CT data. For each view, measurements of the α angle and head-neck offset were obtained by two researchers (intraobserver correlation coefficients of 0.80-0.94 for the α angle and 0.42-0.80 for the head-neck offset measurements). The relationships between radiographic measurements from each view and the 3-D shape scores (for the entire proximal femur and for the region specific to the cam lesion) were assessed with linear correlation. Additionally, partial least squares regression was used to determine which combination of views and measurements was the most effective at predicting 3-D shape scores.

Results Three-dimensional shape scores were most strongly correlated with α angle on the cross-table view when considering the entire proximal femur (r = -0.568; p < 0.001) and on the Meyer lateral view when considering the region of the cam lesion (r = -0.669; p < 0.001). Partial least squares regression demonstrated that measurements from the Meyer lateral and 90° Dunn radiographs produced the optimized regression model for predicting shape scores for the proximal femur (R2 = 0.405, root mean squared error of prediction [RMSEP] = 1.549) and the region of the cam lesion (R2 = 0.525, RMSEP = 1.150). Interestingly, views with larger differences in the α angle and head-neck offset between control and cam FAI groups did not have the strongest correlations with 3-D shape.

Conclusions Considered together, radiographic measurements from the Meyer lateral and 90° Dunn views provided the most effective predictions of 3-D shape of the proximal femur and the region of the cam lesion as determined using shape modeling metrics.

Clinical Relevance Our results suggest that clinicians should consider using the Meyer lateral and 90° Dunn views to evaluate patients in whom cam FAI is suspected. However, the α angle and head-neck offset measurements from these and other plain film views could describe no more than half of the overall variation in the shape of the proximal femur and cam lesion. Thus, caution should be exercised when evaluating femoral head anatomy using the α angle and head-neck offset measurements from plain film radiographs. Given these findings, we believe there is merit in pursuing research that aims to develop the framework necessary to integrate statistical shape modeling into clinical evaluation, because this could aid in the diagnosis of cam FAI.

P. R. Atkins, J. A. Weiss, S. K. Aoki, C. L. Peters, A. E. Anderson, Department of Orthopaedics, University of Utah, Salt Lake City, UT, USA

P. R. Atkins, Y. Shin, R. T. Whitaker, J. A. Weiss, C. L. Peters, A. E. Anderson, Department of Bioengineering, University of Utah, Salt Lake City, UT, USA

P. Agrawal, S. Y. Elhabian, R. T. Whitaker, J. A. Weiss, A. E. Anderson, Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA

P. Agrawal, S. Y. Elhabian, R. T. Whitaker, J. A. Weiss, School of Computing, University of Utah, Salt Lake City, UT, USA

A. E. Anderson, Department of Physical Therapy, Department of Orthopaedic Surgery, University of Utah, 590 Wakara Way, Room A100, Salt Lake City, UT 84108, USA, email: Andrew.Anderson@hsc.utah.edu

The institution of one or more of the authors has received, during the study period, funding from the National Institutes of Health (R01-EB016701 [AEA], P41-GM103545 [RTW], R01-GM083925 [JAW], R21-AR063844 [AEA]) and the LS-Peery Discovery Program in Musculoskeletal Research (PRA). One of the authors (SKA) received personal fees from Stryker Medical (Kalamazoo, MI, USA), outside the submitted work. One of the authors (CLP) received personal fees from Zimmer Biomet (Warsaw, IN, USA) and from CoNextions Medical (Salt Lake City, UT, USA), outside the submitted work.

All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research® editors and board members are on file with the publication and can be viewed on request.

Clinical Orthopaedics and Related Research® neither advocates nor endorses the use of any treatment, drug, or device. Readers are encouraged to always seek additional information, including FDA approval status, of any drug or device before clinical use.

Each author certifies that his or her institution approved the human protocol for this investigation and that all investigations were conducted in conformity with ethical principles of research.

Received March 22, 2018

Accepted July 31, 2018

© 2019 Lippincott Williams & Wilkins LWW
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