Predictive Value of Dual-Energy CT-Derived Metrics for the Use of Bone Substitutes in Distal Radius Fracture Surgery

Author:

Reschke Philipp1ORCID,Koch Vitali1ORCID,Mahmoudi Scherwin1,Booz Christian1,Yel Ibrahim1,Gotta Jennifer1ORCID,Stahl Adrian1,Reschke Robin2,Scholtz Jan-Erik1,Martin Simon S.1,Gruber-Rouh Tatjana1,Eichler Katrin1,Vogl Thomas J.1ORCID,Gruenewald Leon D.1ORCID

Affiliation:

1. Department of Diagnostic and Interventional Radiology, Clinic for Radiology and Nuclear Medicine, Hospital of the Goethe University Frankfurt, 60590 Frankfurt am Main, Germany

2. Department of Dermatology and Venereology, University Medical Center Hamburg-Eppendorf, 20537 Hamburg, Germany

Abstract

(1) Background: Low bone mineral density (BMD) is a significant risk factor for complicated surgery and leads to the increased use of bone substitutes in patients with distal radius fractures (DRFs). No accepted model has yet been established to predict the use of bone substitutes to facilitate preoperative planning. (2) Methods: Unenhanced dual-energy CT (DECT) images of DRFs were retrospectively acquired between March 2016 and September 2020 using the internal PACS system. Available follow-up imaging and medical health records were reviewed to determine the use of bone substitutes. DECT-based BMD, trabecular Hounsfield units (HU), cortical HU, and cortical thickness ratio were measured in non-fractured segments of the distal radius. Diagnostic accuracy parameters were calculated for all metrics using receiver-operating characteristic (ROC) curves and associations of all metrics with the use of bone substitutes were evaluated using logistic regression models. (3) The final study population comprised 262 patients (median age 55 years [IQR 43–67 years]; 159 females, 103 males). According to logistic regression analysis, DECT-based BMD was the only metric significantly associated with the use of bone substitutes (odds ratio 0.96, p = 0.003). However, no significant associations were found for cortical HU (p = 0.06), trabecular HU (p = 0.33), or cortical thickness ratio (p = 0.21). ROC-curve analysis revealed that a combined model of all four metrics had the highest diagnostic accuracy with an area under the curve (AUC) of 0.76. (4) Conclusions: DECT-based BMD measurements performed better than HU-based measurements and cortical thickness ratio. The diagnostic performance of all four metrics combined was superior to that of the individual parameters.

Publisher

MDPI AG

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