Jerry Y Du1, Christopher D Flanagan1, Jay S Bensusan2, Konrad D Knusel1, Ozan Akkus1,2, Clare M Rimnac1,2. 1. Department of Orthopedic Surgery, University Hospitals Cleveland Medical Center and Case Western Reserve University School of Medicine, Cleveland, Ohio. 2. Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, Ohio.
Abstract
BACKGROUND: Structural bone allografts are an established treatment method for long-bone structural defects resulting from such conditions as traumatic injury and sarcoma. The functional lifetime of structural allografts depends on resistance to cyclic loading (cyclic fatigue life), which can lead to fracture at stress levels well below the yield strength. Raman spectroscopy biomarkers can be used to non-destructively assess the 3 primary components of bone (collagen, mineral, and water), and may aid in optimizing allograft selection to decrease fatigue fracture risk. We studied the association of Raman biomarkers with the cyclic fatigue life of human allograft cortical bone. METHODS: Twenty-one cortical bone specimens were machined from the femoral diaphyses of 4 human donors (a 63-year old man, a 61-year-old man, a 51-year-old woman, and a 48-year-old woman) obtained from the Musculoskeletal Transplant Foundation. Six Raman biomarkers were analyzed: collagen disorganization, mineral maturation, matrix mineralization, and 3 water compartments. The specimens underwent cyclic fatigue testing under fully reversed conditions (35 and 45 MPa), during which they were tested to fracture or to 30 million cycles ("runout"), simulating 15 years of moderate activity. A tobit censored linear regression model for cyclic fatigue life was created. RESULTS: The multivariate model explained 60% of the variance in the cyclic fatigue life (R = 0.604, p < 0.001). Increases in Raman biomarkers for disordered collagen (coefficient: -2.74×10, p < 0.001) and for loosely collagen-bound water compartments (coefficient: -2.11×10, p < 0.001) were associated with a decreased cyclic fatigue life. Increases in Raman biomarkers for mineral maturation (coefficient: 3.50×10, p < 0.001), matrix mineralization (coefficient: 2.32×10, p < 0.001), tightly collagen-bound water (coefficient: 1.19×10, p < 0.001), and mineral-bound water (coefficient: 3.27×10, p < 0.001) were associated with an increased cyclic fatigue life. Collagen disorder accounted for 44% of the variance in the cyclic fatigue life, mineral maturation accounted for 6%, and all bound water compartments accounted for 3%. CONCLUSIONS: Increasing baseline collagen disorder was associated with a decreased cyclic fatigue life and had the strongest correlation with the cyclic fatigue life of human cortical donor bone. This model should be prospectively validated. CLINICAL RELEVANCE: Raman analysis is a promising tool for the non-destructive evaluation of structural bone allograft quality for load-bearing applications.
BACKGROUND: Structural bone allografts are an established treatment method for long-bone structural defects resulting from such conditions as traumatic injury and sarcoma. The functional lifetime of structural allografts depends on resistance to cyclic loading (cyclic fatigue life), which can lead to fracture at stress levels well below the yield strength. Raman spectroscopy biomarkers can be used to non-destructively assess the 3 primary components of bone (collagen, mineral, and water), and may aid in optimizing allograft selection to decrease fatigue fracture risk. We studied the association of Raman biomarkers with the cyclic fatigue life of human allograft cortical bone. METHODS: Twenty-one cortical bone specimens were machined from the femoral diaphyses of 4 human donors (a 63-year old man, a 61-year-old man, a 51-year-old woman, and a 48-year-old woman) obtained from the Musculoskeletal Transplant Foundation. Six Raman biomarkers were analyzed: collagen disorganization, mineral maturation, matrix mineralization, and 3 water compartments. The specimens underwent cyclic fatigue testing under fully reversed conditions (35 and 45 MPa), during which they were tested to fracture or to 30 million cycles ("runout"), simulating 15 years of moderate activity. A tobit censored linear regression model for cyclic fatigue life was created. RESULTS: The multivariate model explained 60% of the variance in the cyclic fatigue life (R = 0.604, p < 0.001). Increases in Raman biomarkers for disordered collagen (coefficient: -2.74×10, p < 0.001) and for loosely collagen-bound water compartments (coefficient: -2.11×10, p < 0.001) were associated with a decreased cyclic fatigue life. Increases in Raman biomarkers for mineral maturation (coefficient: 3.50×10, p < 0.001), matrix mineralization (coefficient: 2.32×10, p < 0.001), tightly collagen-bound water (coefficient: 1.19×10, p < 0.001), and mineral-bound water (coefficient: 3.27×10, p < 0.001) were associated with an increased cyclic fatigue life. Collagen disorder accounted for 44% of the variance in the cyclic fatigue life, mineral maturation accounted for 6%, and all bound water compartments accounted for 3%. CONCLUSIONS: Increasing baseline collagen disorder was associated with a decreased cyclic fatigue life and had the strongest correlation with the cyclic fatigue life of human cortical donor bone. This model should be prospectively validated. CLINICAL RELEVANCE: Raman analysis is a promising tool for the non-destructive evaluation of structural bone allograft quality for load-bearing applications.
Authors: Gurjit S Mandair; Mohammed P Akhter; Francis W L Esmonde-White; Joan M Lappe; Susan P Bare; William R Lloyd; Jason P Long; Jessica Lopez; Kenneth M Kozloff; Robert R Recker; Michael D Morris Journal: Bone Date: 2021-04-14 Impact factor: 4.626