Fracture healing is one of the most frequently employed scenarios for studies of the effects the local mechanical environment on skeletal tissue differentiation. Mechanical
loading of a fracture callus occurs most commonly as a consequence of weight bearing; however, dynamization, or applied micromotion, of the fracture gap has also been investigated. Results of these studies have shown that the effects of loading depend heavily on the mode [35], rate [36], and magnitude of loading [37], as well as gap size [37]
and the time during healing at which the dynamization is enacted (eg, [38]). Application of cyclic compressive dis- placements can enhance healing through increased callus formation and more rapid ossification and bridging [39].
However, the benefits of applied cyclic compressive dis- placements appear to be limited to displacements that induce an interfragmentary strain (defined as the ratio of applied displacement to the gap size) of 7% or less [35,37].
Moreover, dynamization of the fracture gap appears to be detrimental in the very early stage of healing [38], yet beneficial during later stages [40,41].
As evidenced by the success of distraction osteogenesis in both experimental and clinical settings, application of successive tensile displacements across an osteotomy gap can also promote bone formation. In contrast to the effects of cyclic compressive loading, however, bone formation in distraction osteogenesis occurs primarily via intramem- branous ossification. These characteristics of distraction also appear to hold when the tensile displacements are applied for only 2 days at a time, followed by shortening of the osteotomy gap to its original length [42], but not when the tensile displacements are applied in a true oscillatory manner (eg, 1 to 10 Hz frequency) [35]. The effects of shear or transverse movement at the fracture site are controver- sial [43]. Studies investigating the use of a bending motion to an osteotomy gap reported formation of cartilage rather than bone within the gap [44].
In parallel with some of the earlier experimental inves- tigations summarized earlier, and Perren and Cordey [45]
proposed the interfragmentary strain theory, which states that only tissue that is capable of withstanding the pre- sent value of interfragmentary strain can form in the fracture gap. This theory is consistent with observations that granulation tissue forms initially in the gap, followed by cartilage and then bone. The successive formation of each type of tissue further reduces the interfragmentary strain that occurs as a result of the applied load and allows a stiffer tissue to form next.
The interfragmentary strain theory presents an over- simplified description of the mechanical environment within the fracture gap in that it uses one scalar (inter- fragmentary strain) to describe a multiaxial strain field that varies as a function of position within the gap.
More recent models of the mechanobiology of skeletal tissue differentiation have sought to account for this complexity by considering the distributions of local mechanical stimuli present throughout the fracture gap (Fig. 14.5A–C) [46–48] and the interplay between osteogenesis and angiogenesis (Fig. 14.5D) [49]. Carter and colleagues have proposed that different combina- tions of hydrostatic pressure and tensile strain promote the formation of different skeletal tissues [46], while Claes and Heigle have postulated that these two Fig. 14.4. An application of RUST scores to each of the four
cortices visible on the anterior–posterior and lateral radiographs of a tibial shaft fracture. The RUST score for this callus was 8 out of a maximum of 12. The score for each cortex was: medial cortex (RUST = 2), lateral cortex (RUST = 3), anterior cortex (RUST = 2), and posterior cortex (RUST = 1). Source: [33] (images not to scale).
Reproduced with permission of Lippincott Williams & Wilkins.
stimuli regulate intramembranous versus endochon- dral ossification [47]. Shefelbine and colleagues adapted this model to also include bone resorption and tissue failure [30]. Lacroix and Prendergast have instead proposed that the two key stimuli are shear strain and fluid flow [48]. Direct comparison of these models’ pre- dictions to histological analyses of bone healing, and also experimental measurement of local mechanical
stimuli such as shear strain within a bone defect, sug- gests that the most accurate predictions are those based on shear strain and fluid flow [44,50]. However, each of these theories is unable to predict certain histologi- cal features of the fracture healing process [48,50]
indicating that the definitive role of the local mechani- cal environment in modulating healing has yet to be elucidated fully.
Principal tensile strain history
Fibro-
cartilage Fibrous tissue Tension line
Cartilage
Pressure line
(–) Compression Tension (+)
Hydrostatic stress history 0
Bone (A)
Strain [%]
15
–0.15 5
–5 –15
Connective tissue or fibrocartilage Intramembranous ossification Endochondral ossification
Hydrostatic pressure [MPa]
0.15 (B)
Fluid flow
Fluid flow
Tissue shear strain
Resorption Granulation tissue
(mesenchymal cells)
Time = 0
Time
Bone Cartilage
Fibrous connective
tissue (C)
Tissue shear strain
Resorption Granulation tissue
(mesenchymal cells)
Time = 0
Time
Bone Cartilage
Fibrous connective
tissue
Rules:
IF (S = ‘bone’ AND O
2low) THEN CARTILAGE
IF (S = ‘bone’ AND O
2high) THEN BONE
(D)
Fig. 14.5. Models of the mechanobiology of skeletal tissue differentiation by: (A) Carter and colleagues; (B) Claes and Heigle; (C) Lacroix and Prendergast; and (D) Checa and Prendegast. (A) Source: [46]. Reproduced with permission of Wolter Kluwer. (B) Source: [47]. Reproduced with permission of Elsevier. (C) Source: [48]. Reproduced with permission of Elsevier. (D) Source: [49].
Reproduced with permission of Springer.
eferences 113
SUMMARY
An essential outcome in fracture healing is restoration of sufficient mechanical integrity to allow weight bearing and activities of daily living. Thus, biomechanical analyses of fracture healing are critical for thorough assessment of the repair process. At present, the biomechanical progression of secondary fracture healing is well characterized, and standardized in vitro methods of quantifying the extent of healing have been established. Noninvasive methods of measuring the regain of bone stiffness have also been reported; however, development of noninvasive methods of measuring the regain of strength has lagged behind.
Studies to date on the effects of mechanical factors indicate that it is possible to augment healing via mechanical load- ing, and the growing body of literature in this area suggests that further enhancements in healing may be possible.
Thus, an understanding of the biomechanics of fracture healing can be applied not only to the assessment of heal- ing but also to development of new repair strategies.
REFERENCES
1. Moss DP, Tejwani NC. Biomechanics of external fixation: a review of the literature. Bull NYU Hosp Joint Dis. 2007;65(4):294–9.
2. Bong MR, Kummer FJ, Koval KJ, et al. Intramedullary nailing of the lower extremity: biomechanics and biology. J Am Acad Orthop Surg. 2007;15(2):97–106.
3. Bottlang M, Schemitsch CE, Nauth A, et al.
Biomechanical concepts for fracture fixation. J Orthop Trauma. 2015;29(suppl 12):S28–33.
4. Steiner M, Volkheimer D, Meyers N, et al. Comparison between different methods for biomechanical assess- ment of ex vivo fracture callus stiffness in small animal bone healing studies. PLoS One. 2015;10(3):e0119603.
5. Foux A, Black RC, Uhthoff HK. Quantitative measures for fracture healing: an in‐vitro biomechanical study.
J Biomech Engin. 1990;112(4):401–6.
6. Tsiridis E, Morgan EF, Bancroft JM, et al. Effects of OP‐1 and PTH in a new experimental model for the study of metaphyseal bone healing. J Orthop Res. 2007;25(9):
1193–203.
7. Leong PL, Morgan EF. Measurement of fracture callus material properties via nanoindentation. Acta Biomater.
2008;4(5):1569–75.
8. Manjubala I, Liu Y, Epari DR, et al. Spatial and temporal variations of mechanical properties and mineral content of the external callus during bone healing. Bone.
2009;45(2):185–92.
9. White AA 3rd, Panjabi MM, Southwick WO. The four biomechanical stages of fracture repair. J Bone Joint Surg. 1977;59(2):188–92.
10. Ellegaard M, Kringelbach T, Syberg S, et al. The effect of PTH (1‐34) on fracture healing during different loading conditions. J Bone Miner Res. 2013;28(10):2145–55.
11. Kakar S, Einhorn TA, Vora S, et al. Enhanced chondrogen- esis and Wnt‐signaling in parathyroid hormone treated fractures. J Bone Miner Res. 2007;22(12):1903–12.
12. Li YF, Luo E, Feng G, et al. Systemic treatment with stron- tium ranelate promotes tibial fracture healing in ovariec- tomized rats. Osteoporos Int. 2010;21(11):1889–97.
13. Nyman JS, Munoz S, Jadhav S, et al. Quantitative measures of femoral fracture repair in rats derived by micro‐
computed tomography. J Biomech. 2009;42(7):891–7.
14. Little DG, McDonald M, Bransford R, et al. Manipulation of the anabolic and catabolic responses with OP‐1 and zoledronic acid in a rat critical defect model. J Bone Miner Res. 2005;20(11):2044–52.
15. Hao Y, Wang X, Wang L, et al. Zoledronic acid sup- presses callus remodeling but enhances callus strength in an osteoporotic rat model of fracture healing. Bone.
2015;81:702–11.
16. Hegde V, Jo J, Andreopoulou P, et al. Effect of osteoporo- sis medications on fracture healing. Osteoporos Int.
2016;27(3):861–71.
17. Hente R, Cordey J, Perren SM. In vivo measurement of bending stiffness in fracture healing. Biomed Engin Online. 2003;2:8.
18. Richardson JB, Cunningham JL, Goodship AE, et al.
Measuring stiffness can define healing of tibial fractures.
J Bone Joint Surg Br. 1994;76(3):389–94.
19. Claes LE, Cunningham JL. Monitoring the mechanical properties of healing bone. Clin Orthop Relat Res.
2009;467(8):1964–71.
20. Aarnes GT, Steen H, Ludvigsen P, et al. In vivo assessment of regenerate axial stiffness in distraction osteogenesis. J Orthop Res. 2005;23(2):494–8.
21. Watanabe Y, Takai S, Arai Y, et al. Prediction of mechan- ical properties of healing fractures using acoustic emis- sion. J Orthop Res. 2001;19(4):548–53.
22. Tower SS, Beals RK, Duwelius PJ. Resonant frequency analysis of the tibia as a measure of fracture healing. J Orthop Trauma. 1993;7(6):552–7.
23. Gerlanc M, Haddad D, Hyatt GW, et al. Ultrasonic study of normal and fractured bone. Clin Orthop Relat Res.
1975;111:175–80.
24. Glinkowski W, Gorecki A. Clinical experiences with ultrasonometric measurement of fracture healing.
Technol Health Care. 2006;14(4–5):321–33.
25. Dodd SP, Miles AW, Gheduzzi S, et al. Modelling the effects of different fracture geometries and healing stages on ultra- sound signal loss across a long bone fracture. Comput Methods Biomech Biomed Engin. 2007;10(5):371–5.
26. Jamsa T, Koivukangas A, Kippo K, et al. Comparison of radiographic and pQCT analyses of healing rat tibial fractures. Calcif Tissue Int. 2000;66(4):288–91.
27. Nazarian A, Pezzella L, Tseng A, et al. Application of structural rigidity analysis to assess fidelity of healed fractures in rat femurs with critical defects. Calcif Tissue Int. 2010;86(5):397–403.
28. Grigoryan M, Lynch JA, Fierlinger AL, et al. Quantitative and qualitative assessment of closed fracture healing using computed tomography and conventional radiogra- phy. Acad Radiol. 2003;10(11):1267–73.
29. Kuhlman JE, Fishman EK, Magid D, et al. Fracture non- union: CT assessment with multiplanar reconstruction.
Radiology. 1988;167(2):483–8.
30. Shefelbine SJ, Simon U, Claes L, et al. Prediction of frac- ture callus mechanical properties using micro‐CT images and voxel‐based finite element analysis. Bone.
2005;36(3):480–8.
31. Histing T, Kristen A, Roth C, et al. In vivo gait analysis in a mouse femur fracture model. J Biomech.
2010;43(16):3240–3.
32. Morshed S. Current options for determining fracture union. Adv Med. 2014;2014:Article ID 708574.
33. Whelan DB, Bhandari M, Stephen D, et al. Development of the radiographic union score for tibial fractures for the assessment of tibial fracture healing after intramedullary fixation. J Trauma Acute Care Surg. 2010;68(3):629–32.
34. Litrenta J, Tornetta P III, Mehta S, et al. Determination of radiographic healing: an assessment of consistency using RUST and modified RUST in metadiaphyseal frac- tures. J Orthop Trauma. 2015;29(11):516–20.
35. Augat P, Merk J, Wolf S, Claes L. Mechanical stimula- tion by external application of cyclic tensile strains does not effectively enhance bone healing. J OrthopTtrauma.
2001;15(1):54–60.
36. Wolf S, Augat P, Eckert‐Hubner K, et al. Effects of high‐
frequency, low‐magnitude mechanical stimulus on bone healing. Clin Orthop. 2001;385:192–8.
37. Claes L, Augat P, Suger G, et al. Influence of size and stability of the osteotomy gap on the success of fracture healing. J Orthop Res. 1997;15(4):577–84.
38. Claes L, Blakytny R, Gockelmann M, et al. Early dynam- ization by reduced fixation stiffness does not improve fracture healing in a rat femoral osteotomy model.
J Orthop Res. 2009;27(1):22–7.
39. Goodship AE, Kenwright J. The influence of induced micromovement upon the healing of experimental tibial fractures. J Bone Joint Surg Br. 1985;67(4):650–5.
40. Boerckel JD, Uhrig BA, Willett NJ, et al. Mechanical regulation of vascular growth and tissue regeneration in vivo. Proc Natl Acad Sci U S A. 2011;108(37):E674–80.
41. Gardner MJ, van der Meulen MC, Demetrakopoulos D, et al. In vivo cyclic axial compression affects bone healing in the mouse tibia. J Orthop Res. 2006;24(8):1679–86.
42. Claes L, Augat P, Schorlemmer S, et al. Temporary dis- traction and compression of a diaphyseal osteotomy accel- erates bone healing. J Orthop Res. 2008;26(6):772–7.
43. Schell H, Epari DR, Kassi JP, et al. The course of bone healing is influenced by the initial shear fixation stability.
J Orthop Res. 2005;23(5):1022–8.
44. Miller GJ, Gerstenfeld LC, Morgan EF. Mechanical micro- environments and protein expression associated with for- mation of different skeletal tissues during bone healing.
Biomech Model Mechanobiol. 2015;14(6):123––53.
45. Perren SM, Cordey J. The concept of interfragmentary strain. In: Uhthoff HK (ed.) Current Concepts of Internal Fixation of Fractures. Berlin: Springer, 1980, pp. 63–77.
46. Carter DR, Beaupre GS, Giori NJ, et al. Mechanobiology of skeletal regeneration. Clin Orthop. 1998(suppl 355):S41–55.
47. Claes LE, Heigele CA. Magnitudes of local stress and strain along bony surfaces predict the course and type of fracture healing. J Biomech. 1999;32(3):255–66.
48. Lacroix D, Prendergast PJ. A mechano‐regulation model for tissue differentiation during fracture healing: analysis of gap size and loading. J Biomech. 2002;35(9):1163–71.
49. Checa S, Prendergast PJ. A mechanobiological model for tissue differentiation that includes angiogenesis: a lat- tice‐based modeling approach. Ann Biomed Engin. 2009;
37(1):129–45.
50. Isaksson H, Wilson W, van Donkelaar CC, et al.
Comparison of biophysical stimuli for mechano‐regula- tion of tissue differentiation during fracture healing.
J Biomech. 2006;39(8):1507–16.
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