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Orthopedic and Rehabilitation Engineering

Orthopedic and Rehabilitation Engineering - Poster Session A

Poster K8 - Can DEXA Predict Metatarsal Bone Quality in Runners Affected by the Female Athlete Triad?

Thursday, October 24, 2024

10:00 AM - 11:00 AM EST

Location: Exhibit Hall E, F & G

Presenting Author(s)

Amelia Adin

Undergraduate Research Assistant
University of Florida
Newberry, Florida, United States

Co-Author(s)

JN

Julia Nicolescu

PhD Candidate
Worcester Polytechnic Institute, United States
AW

Andrew Wilzman

PhD Candidate
Worcester Polytechnic Institute, United States
Adam Tenforde, MD (he/him/his)

Associate Professor
Harvard Medical School
Cambridge, Massachusetts, United States
ID

Irene Davis

Professor
University of South Forida, United States

Primary Investigator(s)

Karen Troy, PhD (she/her/hers)

Professor, Associate Department Head
Worcester Polytechnic Institute
Worcester, Massachusetts, United States

Introduction: Up to 74.7% of young female athletes are at moderate or high risk of the Female Athlete Triad [1]. The Triad is characterized by a low energy availability, menstrual dysfunction, and low bone mineral density (BMD) [2, 3], which leaves affected athletes vulnerable to bone stress injuries (BSIs). Sports that emphasize leanness and endurance, such as running, have a higher prevalence of the Triad [4]. Dual energy X-ray absorptiometry (DEXA) scans are used to confirm a Triad diagnosis by measuring BMD of the total body, at the hip, the lumbar spine, and the distal forearm. Although up to 38% of BSIs in college athletes occur in the metatarsals [5], this area is not assessed by a DEXA scan. Here, we examined relationships between metatarsal bone micro- and macrostructure and DEXA measures in female runners to determine the degree to which DEXA could predict metatarsal bone quality. Female Athlete Triad risk was also determined for each participant. We hypothesized that DEXA measures would be positively associated with measures of metatarsal quality, and that higher Triad risk (low, moderate, or high) would be associated lower with bone quality by both DEXA and in the metatarsals.

Materials and

Methods: Thirty-three female runners each with a weekly running volume of at least 10 miles for the last year and aged 17-41 years participated in this institutionally approved study. We collected high resolution peripheral quantitative computed tomography (HRpQCT) scans of the distal 2nd metatarsal (XtremeCT I, Scanco, Switzerland), DEXA scans, and Triad risk assessments. ¬ Low-resolution (voxel size 246 µm) CT scans of whole metatarsals were processed using Mimics (Version 24.0, Materialise, Belgium) software to generate a segmented mask of the left 2nd metatarsal. This mask was processed in MATLAB to extract measures of size, shape, and mineral content [6]. High-resolution (voxel size 82 microns) scans of the 10-20% distal region of the second metatarsal were evaluated with Scanco XtremeCT I software to extract measures of microstructure and density [7]. All measures obtained from low- and high-resolution scans are outlined in Table 1. DEXA scans assessed areal BMD (aBMD) of the total body, femoral neck, lumbar spine, and distal forearm, and reported lean and fat body mass. The Triad risk assessment questionnaire consisted of ten questions compiled from the 2014 Female Athlete Triad Coalition Consensus Statement [2]. Answers to this questionnaire and Z-scores from the DEXA scans were used to assign participants a risk score that classified them as low (0-1), moderate (2-5), or high risk (6-12) [2]. Ten participants were not scored for Triad risk due to incomplete questionnaire or DEXA data. A Pearson’s correlation test was performed between 26 metatarsal bone quality measures and 6 DEXA measures.

Results, Conclusions, and Discussions: We observed a significant positive association (r=0.529, p=0.018) between lowest DEXA-reported Z-scores and metatarsal compressive strength index (CSI; Figure 1A). Z-scores and aBMD at the forearm and hip had weak to moderate correlations with metatarsal CSI, bone mineral content and volumetric BMD (r=0.282–0.429), though lowest Z-score had the highest correlations with these three measures (r=0.429-0.529). Measures of bone size and shape had very low associations with DEXA measures (r < 0.200), though some microstructure measures had weak correlations (r < 0.400) with DEXA aBMD and Z-scores (Figure 2). Of the DEXA measures, lowest Z-score was the best predictor of metatarsal bone health (Figure 2), which supports current Triad diagnosis procedures. It is worth noting that the average lowest Z-score in our group of female runners was -0.734 (SD=0.653), which is significantly (p < 0.001) below the expected average Z-score of 0.0 for healthy, age-matched adults.

Body fat percentage was inversely related to metatarsal measures, with higher fat percentage being associated with poorer bone quality. For example, greater trabecular spacing had a significant correlation with body fat percentage (r=0.485, p=0.051) (Figure 1B). Although very low body fat is associated with low energy availability in the Female Athlete Triad, our cohort may not contain enough athletes at low body fat to show such associations. Within our sample, low body fat percentage may be associated with general fitness and better bone quality.

Although DEXA measures were moderately predictive of metatarsal bone health, Triad risk scores showed no clear distributions among the data comparisons (Figure 1). In fact, risk scores seemed to be evenly scattered between high and low DEXA and metatarsal bone quality. However, most of our participants were in the moderate risk category. The Triad Coalition risk assessment accounts for a variety of past and present factors that affect bone metabolism, and not all these factors may influence our measures of metatarsal bone quality. Additionally, this cohort may not be representative of the greater population of female runners since participants were recruited for an ongoing study requiring them to either have a current metatarsal BSI or no history of BSI.

Acknowledgements (Optional): This work was funded by NSF grant EEC2150076 and NIH grant R15HD104169.

References

[1] J. J. Koltun, N. C. Strock, E. A. Southmayd, A. P. Oneglia, N. I. Williams and M. J. De Souza, "Comparison of Female Athlete Triad COalition and RED-S risk assessment tools," Journal of Sports Sciences, 2019.
[2] M. J. De Souza, A. Nattiv, E. Joy, M. Mirsa, N. I. Williams, R. J. Mallinson, J. C. Gibbs, M. Olmsted, M. Goolsby and G. Matheson, "2014 Female Athlete Triad Coalition Consensus Statement on Treatment and Return to Play of the Female Athlete Triad," Br J Sports Med, vol. 48, no. 289, 2014.
[3] J. Maya and M. Mirsa, "The Female Athlete Triad: Review of Current Literature," Curr Opin Endocrinol Diabetes Obes, vol. 22, no. 1, 2022.
[4] T. G. Nazem and K. E. Ackerman, "The Female Athlete Triad," Sports Health, vol. 4, no. 4, pp. 302-311, 2012.
[5] K. H. Rizzone, K. E. Ackerman, K. G. Roos, T. P. Dompier and Z. Y. Kerr, "The Epidemiollogy of Stress Fractures in Collegiate Student-Athletes, 2004-2005 Through 2013-2014 Academic Years," Journal of Athletic Training, vol. 52, no. 10, pp. 966-975, 2017.
[6] W. B. Edwards, T. J. Schnitzer and K. L. Troy, "Bone Mineral and Stiffness Loss at the Distal Femur and Proximal Tibia in Acute Spinal Cord Injury," Osteoporosis International, vol. 25, pp. 1005-1015, 2014.
[7] M. L. Bouxsein, S. K. Boyd, B. A. Christiansen, R. E. Guldberg, K. J. Jepsen and R. Müller, "Guidelines for Assessment of Bone Microstructure in Rodents Using Micro-Computed Tomography," J Bone Miner Res, vol. 25, no. 7, pp. 1468-1486, 2010.