Distal radius fractures (DRFs) are commonly treated non-operatively with cast immobilization; however, there are no standardized clinical practice guidelines to direct optimal duration of immobilization following a DRF. Finite element (FE) modelling coupled with highresolution peripheral quantitative computed tomography (HR-pQCT) allows for non-invasive in vivo assessment of bone density and stiffness throughout the fracture healing process, which may inform fracture healing progression and cast removal. Many fracture assessment instruments have been developed for clinical use, but a lack of validation and standardization has led to considerable variability in the assessment of fracture healing. We hypothesized that changes in bone stiffness and bone mineral density measured using HR-pQCT can better inform the duration of casting following a DRF. We aimed to identify clinical assessment instruments that were good predictors of fracture stiffness and could inform cast removal.
Participants (n=30) with a stable DRF were followed for two week intervals from the time of fracture until two months post-fracture, then at three months and six months post-fracture. At each follow-up, participants underwent clinical, radiographic, and functional assessments, as well as had their fractured wrist scanned using HR-pQCT. Recovery of bone stiffness during fracture healing was determined from micro-FE (µFE) models generated from HR-pQCT image data.
During fracture healing, significant longitudinal changes were found in µFE-estimated stiffness, patient-reported outcomes, grip strength, range of motion (ROM), tenderness, number of cortices healed based on radiographs, and fracture line visibility (p<0.05); however, no significant change was detected in HR-pQCT based total bone mineral density. Grip strength, ROM, and patient-reported outcomes such as the Patient-Rated Wrist Evaluation (PRWE) and the Quick Disability of the Arm, Shoulder and Hand (QuickDASH) questionnaire correlated strongly with µFE-estimated stiffness (0.61≥ rm ≥0.71). Based on µFE-estimated stiffness, PRWE and QuickDASH are the best predictors of stiffness recovery (p<0.05) and may be used to guide duration of cast immobilization in the clinical setting.
|1992||Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36), I: conceptual framework and item selection. Med Care. June 1992;30(6):473-483.|
|2003||Ahlborg HG, Johnell O, Turner CH, Rannevik G, Karlsson MK. Bone loss and bone size after menopause. NEJM. July 24, 2003;349(4):327-334.|
|2020||Suzuki T, Matsuura Y, Yamazaki T, Akasaka T, Ozone E, Matsuyama Y, Mukai M, Ohara T, Wakita H, Taniguchi S, Ohtori S. Biomechanics of callus in the bone healing process, determined by specimen-specific finite element analysis. Bone. March 2020;132:115212.|
|2008||MacNeil JA, Boyd SK. Bone strength at the distal radius can be estimated from high-resolution peripheral quantitative computed tomography and the finite element method. Bone. 2008;42(6):1203-1213.|
|2013||Zysset PK, Dall'Ara E, Varga P, Pahr DH. Finite element analysis for prediction of bone strength. BoneKEy Rep. August 2013;2:386.|
|2010||Burghardt AJ, Issever AS, Schwartz AV, Davis KA, Masharani U, Majumdar S, Link TM. High-resolution peripheral quantitative computed tomographic imaging of cortical and trabecular bone microarchitecture in patients with type 2 diabetes mellitus. J Clin Endocrinol Metab. 2010;95(11):5045-5055.|
|2012||Pauchard Y, Liphardt A-M, Macdonald HM, Hanley DA, Boyd SK. Quality control for bone quality parameters affected by subject motion in high-resolution peripheral quantitative computed tomography. Bone. June 2012;50(6):1304-1310.|
|2019||Burt LA, Billington EO, Rose MS, Raymond DA, Hanley DA, Boyd SK. Effect of high-dose vitamin D supplementation on volumetric bone density and bone strength: a randomized clinical trial. JAMA. August 27, 2019;322(8):736-745.|
|2006||Hadjidakis DJ, Androulakis II. Bone remodeling. Annals NY Acad Sci. December 2006;1092(1):385-396.|
|2012||Tassani S, Matsopoulos GK, Baruffaldi F. 3D identification of trabecular bone fracture zone using an automatic image registration scheme: a validation study. J Biomech. July 26, 2012;45(11):2035-2040.|
|1995||Cummings SR, Nevitt MC, Browner WS, Stone K, Fox KM, Ensrud KE, Cauley J, Black D, Vogt TM; Study of Osteoporotic Fractures Research Group. Risk factors for hip fracture in white women. NEJM. March 23, 1995;332(12):767-773.|
|2001||Homminga J, Huiskes R, Van Rietbergen B, Rüegsegger P, Weinans H. Introduction and evaluation of a gray-value voxel conversion technique. J Biomech. April 2001;34(4):513-517.|
|1978||Lips P, Courpron P, Meunier PJ. Mean wall thickness of trabecular bone packets in the human iliac crest: changes with age. Calcif Tiss Res. 1978;26(1):13-17.|
|2011||Marsell R, Einhorn TA. The biology of fracture healing. Injury. June 2011;42(6):551-555.|
|2005||Shefelbine SJ, Simon U, Claes L, Gold A, Gabet Y, Bab I, Müller R, Augat P. Prediction of fracture callus mechanical properties using micro-CT images and voxel-based finite element analysis. Bone. March 2005;36(3):480-488.|
|2015||van Rietbergen B, Ito K. A survey of micro-finite element analysis for clinical assessment of bone strength: the first decade. J Biomech. March 18, 2015;48(5):832-841.|
|2002||Pistoia W, van Rietbergen B, Lochmüller E-M, Lill CA, Eckstein F, Rüegsegger P. Estimation of distal radius failure load with micro-finite element analysis models based on three-dimensional peripheral quantitative computed tomography images. Bone. June 2002;30(6):842-848.|
|1998||Rho J-Y, Kuhn-Spearing L, Zioupos P. Mechanical properties and the hierarchical structure of bone. Med Eng Phys. 1998;20(2):92-102.|