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Director of Translational Research, New York University, College of Dentistry, 345 East 24th Street, Room 1003 S, New York, NY 10010; edr1{at}nyu.edu
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Abstract |
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 TOP Abstract IntroductionTissue EngineeringBiomaterialsSummaryReferences |
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KEY WORDS: Dental restorations • CAD/CAM • ceramics • tissue engineering • informatics
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Introduction |
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TOPAbstractIntroductionTissue EngineeringBiomaterialsSummaryReferences |
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Tissue Engineering |
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TOPAbstractIntroductionTissue EngineeringBiomaterialsSummaryReferences |
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Influence of implant surface texture on bone response
Experience with endosseous dental implants has been valuable in elucidating the role of surface texture on bone response at the implant-tissue interface (Ricci et al., 2000; Frenkel et al., 2002). Smooth metal, ceramic, or polymer surfaces of orthopedic or dental implants promote thick fibrous encapsulation which may limit—or prevent—bone attachment, while rough surfaces of the same material promote intimate bone integration (Albrektsson et al., 1985; Thomas and Cook 1985; Haddad et al., 1987; McAuslan and Johnson, 1987; Thomas et al., 1987; Linder et al., 1988; Ricci et al., 1991). Rough surfaces enhance platelet attachment (Gemmell and Park, 2000) and fibrin clot adhesions (Davies, 1988), improving the stability of implant-tissue interfaces during collagenous matrix formation and contracture during wound healing. Roughness also affects differentiation, response to biological mediators, and regulatory factors produced by bone cells in vitro (Kieswetter et al., 1996; Batzer et al., 1998; Boyan and Schwartz, 2000).
Cells must attach to spread (Ingber et al., 1986; Re et al., 1994; Chen et al., 1997; Dike et al., 1999), and proliferation is stimulated by spreading (Folkman and Moscona, 1978; Chen et al., 1997). Roughness, however, inhibits spreading. Instead, it drives the attached cells to a more enhanced state of differentiation. Proliferation and differentiation are inversely related. The challenge in scaffold design is to find the balance between these two competing phenomena, providing sufficient roughness for cells to attach while simultaneously promoting spread of the cells to create tissue throughout the entirety of the scaffold and retain the cellular phenotype to create the desired (or required) tissue type(s).
The scale of the roughness is important. To an osteoblast, a rough surface has peak heights greater than 2 µm but less than 10 µm (approximately equal to the cell length) (Ong et al., 1998; Boyan and Schwartz, 2000). In vivo, as surface roughness increases, proliferation of MG63 osteoblast-like cells decreases but differentiation increases (Martin et al., 1995). Osteoblastic morphology and osteocalcin production are correlated with surface roughness. Levels of PGE2 and latent TGF-ß1 both increase with rougher surfaces (Kieswetter et al., 1996; Boyan and Schwartz, 2000), and their production is sensitive to regulation by 1,25-(OH)2D3, a vitamin D metabolite (Boyan et al., 1998). But this effect is not simple: It appears that more mature osteoblasts found on rough surfaces might respond to systemic and local regulatory factors in a different manner than the less mature osteoblasts found on smoother surfaces (Boyan and Schwartz, 2000). Thus, surface roughness is important in establishing the kinds of cells that attach to the implant, and modulates but also influences the rate and extent of phenotypic differentiation. Little is known, however, about the interactions between roughness and material or roughness and other scaffold properties (porosity, pore interconnectivity, etc.).
Influence of directionality of surface texture on bone response
The texture of the surface, as we have seen above, influences the amounts and types of cells that attach to and grow into an implant. Texture can also be used to control the direction of the cell proliferation and spread. This phenomenon, called contact guidance, was first described in 1945 (Weiss, 1945). Cells and matrix molecules have been shown to align with oriented grooves in both polymer and metallic surfaces (Brunette, 1986; Clark and Connolly, 1987; Clark et al., 1990; Chehroudi et al., 1990; Guenard et al., 1991; Schmidt and von Recum, 1992; Brunette and Chehroudi, 1999; Stepien et al., 1999; Walboomers et al., 1999b; Kam et al., 2001). Laser-microgrooved titanium surfaces promote organized bone formation and integration around implants (Ricci et al., 2000; Soboyejo et al., 2002).
As with texture, feature size is important. Micrometric features (features with length scale similar to that of cells) appear to have the most profound effects on cell morphology and behavior (Brunette, 1986; Chehroudi et al., 1990; Clark et al., 1990; Ricci and Alexander, 1992; Schmidt and von Recum, 1992; Ricci et al., 1995; Ricci et al., 1996; Grew et al., 1997, 1998; van Kooten et al., 1998; Frenkel et al., 1999; Walboomers et al., 1999a,b, 2000; Grew and Ricci, 2000). Features with dimensions of 1–15 µm are most effective in eliciting the contact guidance response (Ricci and Alexander, 1992; Ricci et al., 1995; Ricci et al., 1996; van Kooten et al., 1998; Wang et al., 2000).
Contact guidance foreshadows the possibility for rational design of all scaffold features. However, its interaction with other scaffold features has yet to be elucidated.
Influence of porosity on bone response
Another important scaffold feature is porosity. Scaffolds require interconnected pore networks to simulate osteoblast migration and osteoconduction as well as to permit sufficient nutrient support to reach the cells within the scaffold. Bone response to hydroxyapatite (HA) in granular form is dramatically different from that for porous forms (Ripamonte, 2000), despite the use of "powerful" protein inducers (bone morphogenic and osteogenic proteins) to make them equal. In grafted bone, the porosity, not the inherent properties of the graft, determines its survival (Fialkov et al., 2000).
Healing is dependent, in part, on the pore size of the scaffold (Ko et al., 1992). Porous structures that provide large areas that are strain-protected have been shown to promote endosseous integration (Simmons and Pilliar, 2000). Interconnecting porous architecture is one prerequisite for osteoinductivity but, by itself, may not be sufficient to engineer or optimize bone response (de Bruijn et al., 2000). Until now, limitations in fabrication technologies have prevented the influence of this factor from being investigated systematically (Agrawal and Ray, 2001). This, in turn, has led to disagreement about "optimal" pore sizes for bone ingrowth, with reported values ranging from 200 µm to 400 µm (Klawitter and Hulbert, 1971; Pilliar, 1983; Schliephake et al., 1991). Recent investigations with HA fabricated by 3D printing suggest that bone can grow many millimeters into a "solid" block of material which has pores an order of magnitude smaller than that "optimum" size (Dutta Roy, 2003).
Influence of scaffold architecture on bone response
The three-dimensional geometry of scaffold pores also influences tissue response. Investigators have compared bone responses to a series of biodegradable scaffolds with controlled but varied surface chemistry, surface texture, microarchitecture, and design (Simon, 2001; Dutta Roy, 2003; Dutta Roy et al., 2003; Simon et al., 2003). Scaffolds were fabricated from (1) high-molecular-weight (80% by weight) polylactic-co-glycolic acid PLGA with lactic/glycolic ratio of 50:50 and 20% tricalcium phosphate (TCP) (referred to as PLGA for the remainder of the text) and (2) poly(desaminotyrosyl tyrosine ethyl ester carbonate) (referred to as pDTEC for the remainder of the text). Scaffolds 8 mm in diameter and 3 mm thick with radial and vertical channels (right side of Fig. 1
) were fabricated from both PLGA and pDTEC. Scaffolds of the same overall dimensions were fabricated from pDTEC with both channels (left side of Fig. 1) and open channels from both the dural and lateral sides ("waffles" with 500-µm struts with 500-µm pores, as shown in the right side of Fig. 1). Scaffolds were implanted bilaterally in trephine defects in skeletally mature New Zealand white rabbits.
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) at 16 wks. In all configurations, bone grew from the periphery of the implant toward the center, beginning to fill the defect. There is little difference between the bone responses to scaffolds with channels (Figs. 2a, 2b), despite the fact that they were fabricated from different materials. The influence of microarchitecture is immediately apparent when one compares the bone responses to scaffolds with channels and the "waffle" configuration (Figs. 2b, 2c). With the "waffle" configuration, new sites of bone developed throughout the defect. Those new sites proliferate from their periphery at the same rate as bone proliferates at the periphery of the defect, but because there are so many sites, the entire defect will fill more quickly.
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. The struts in the "waffles" shown in Fig. 2d were fabricated to be more porous than those in Fig. 2c. During the ingrowth/scaffold degradation, the "waffle" struts in scaffolds shown in Fig. 2d collapsed, creating bone response with some of the features seen in Fig. 2c, but to a far lesser extent. If microarchitecture features are superimposed on biomaterial composition, bone response to scaffolds could potentially be significantly enhanced.
The challenge for informatics from tissue engineering
Clearly, a complex of factors influences bone response to scaffolds. Much is known about each factor individually. Less is known about the limits over which the factors may be at play (e.g., what pore size and range are most ideal for bone ingrowth? Are they the same for all materials?). Still less is known about interactions between and among these factors; it is likely that they are not independent, and that a subtle change in one could have a significant (or no) influence on others. A fundamental issue that informatics methods could be used to address is how effectively to investigate and, ultimately, describe and predict the cascade of biochemical and cellular reactions that occur as a function of time and implant material: surface texture, microporosity; pore size, dentistry, and connectivity; and three-dimensional configuration.
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Biomaterials |
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Ceramic materials have great appeal for dental restorations because of their esthetics and biocompatibility. However, their full potential for molar crowns and bridges cannot yet be realized. Shaping-induced damage, exacerbated by fatigue damage during normal chewing, dramatically reduces the initial strength of the material, often resulting in catastrophic failure. In monolithic materials, a fundamental trade-off exists: Esthetic (and generally highly brittle) materials are seriously prone to damage, resulting in clinical failure; materials that are tough enough to be damage-tolerant in oral applications are not esthetic. By layering materials, one can overcome the limitations of constituent materials, solving the challenge of addressing the dual, and almost always conflicting, requirements of esthetics and strength.
The quest for high-strength esthetic restorations is not new. For decades, investigators have been exploring factors that would deliver these features in ceramics. Machinable glass ceramics with material properties mimicking those of enamel were introduced (Grossman, 1991), but crowns fabricated from them failed to perform like enamel (Malament and Socransky, 1999a,b). In 1965, McLean suggested that a core material with strength equivalent to that of noble alloy cores would be sufficient. New materials with increasing strength have been introduced over the last decade, some with strength nearly as high as the minimum suggested by McLean. Sadly, failure rates remain disappointingly high (Kelsey et al., 1995; Bochard et al., 1998; Oden et al., 1998; Sjogren et al., 1999; McLaren and White, 2000; Fradeani et al., 2002), still exceeding those of ceramo-metal restorations (Walton 1999).
Crown performance is a complex function of (1) initial material properties, (2) design of the crown and supporting tooth core with the associated stress distributions in response to loading, plus (3) damage introduced by fabrication, shaping, and normal function. Some of the factors that influence performance of molar all-ceramic crowns and challenges for informatics are discussed.
The influence of contact fatigue on crown performance
Ceramic materials used for dental crowns are susceptible, in various degrees, to fatigue. Porcelains are least vulnerable; though their initial strength is not great, neither do they appreciably lose strength when subjected to cyclic loading (then fractured in four-point bending) (Peterson et al., 1998a,b; Jung et al., 2000). Both machinable glass ceramics (Corning, Inc., Corning, NY, USA) and infiltrated alumina (Vita Zahnfabrik, Bad Säckingen, Germany) exhibit interesting behaviors. To a certain number of cycles (approximately 104 cycles at 200-N load for machinable glass ceramics and 105 cycles at 500-N load for infiltrated alumina), there is no degradation in initial strength. Then, suddenly, strength drops precipitously (by as much as 30–50% of the initial strength) and the samples fracture in typical brittle fracture patterns with cone cracks, around but not through the damage zone (for samples greater than 2 mm thick). Specimens loaded (at subcritical loads) beyond that specified number of cycles are able to withstand additional cycling. For those samples, upon loading, fracture occurs at still lower strengths, and the fracture passes through the damage zone beneath the indenter. Even zirconia (St. Gobain/Desmarquest, East Granby, CO, USA), with greatest initial strength, shows fatigue at high contact loads (Jung et al., 2000). If the high-strength but fatigue-vulnerable core of a layered (veneer-core) crown system could be protected from fatigue, crown performance would improve.
Fracture modes and damage initiation
A major challenge for clinicians managing damage of crowns to eliminate catastrophic failure is to understand competing fracture modes. For thick ceramic specimens, Hertzian fracture modes (cone cracks and quasi-plastic yield) dominate and form on the top (loaded) surface; in very thin specimens, flexural fields dominate, resulting in radial fractures from the bottom of the sample (Lawn et al., 2001, 2002). For dentally relevant conditions, what factors influence each mode? Fundamental equations were developed from experimental results indicating that, for monolithic materials, radial cracking (from the flexural surface) is most likely to occur first. The critical load to radial fracture depends on the square of the thickness of the material, and to a lesser degree on the relative moduli of the crown veneer and core and the tooth-supporting structure (Deng, 2003). For thicknesses above 1–1.5 mm, outer surface cone cracks and quasi-plastic yield predominate. Both of these failure modes depend on material properties and radius of the indenter (opposing molar cusp) but are independent of the thickness of the material. When materials are layered, however, some interesting things happen.
Trilayers of glass-ceramic-polycarbonate were fabricated with veneer-core thickness constant at 1.5 mm. Several samples were fabricated with veneer thickness ranging from of 0.5 to 1.25 mm (core thickness, 1.0 to 0.25 mm). When the ceramic layer was either glass-infiltrated alumina (InCeram, Vita Zahnfabrik) or glass-ceramic (Empress II, Ivoclar, Schaan, Liechtenstein), load to first fracture remained approximately constant and always occurred at the lower (cementation) surface of the samples caused by flexure of the ceramic layer (Deng, 2003). For ceramic layers of zirconia, however, with core thickness between 0.3 and 0.6 mm, the first fracture occurred in the glass veneer layer, originating at the glass-zirconia interface (Deng, 2003). Quasi-plastic yield in the zirconia permitted the glass to flex, ultimately developing a radial crack.
Damage at any interface can significantly reduce the strength. In glass-sapphire-polycarbonate trilayers with 1-mm-thick glass and 0.5-mm-thick sapphire, damage on the top surface of the glass results in cone cracks developing at that surface at 700 N (Kim et al., 2003). When the damage is on the bottom surface of the glass (at the sapphire-glass interface), a load of 800 N creates a radial crack originating at the lower surface of the glass and confined within the glass. However, when damage is induced at the lower surface of the sapphire (simulating the cementation surface of a layer crown), radial fracture develops in the sapphire at loads as low as 430 N. Shaping procedures as well as laboratory practices (like sandblasting to clean the crown) and clinical adjustments add damage which undoubtedly further compromises the strength of all-ceramic crowns.
Another factor that could influence crown performance
Cracks in crowns often develop at unexpectedly low loads. This may be related to elastic and/or plastic deformation of the supporting structures (cement and tooth-supporting core) (Hirano and Hirasawa, 1989, 1992, 1994). That deformation builds up a residual tensile stress in the crown at the crown-cement interface. With consecutive loading cycles, stresses increase, ratcheting up the crown stress until fracture occurs (Huang et al., 2000). The degree of creep in resin cements is inversely related to filler loading (Ferracane et al., 1985) and loading (Ferracane et al., 1985; Vaidyanathan et al., 2001). The influence of this factor on crown performance is being investigated.
The challenge for informatics from biomaterials/crown performance
Performance of crowns is a complicated function of an array of variables. As with tissue engineering, much is known about individual factors. Little is known about interactions of those factors. It is easy to evaluate flat samples in a laboratory. It is far more complex and expensive to test real crowns on real teeth. It is exceedingly expensive to obtain unbiased data concerning clinical performance at 10 years, by which time the materials used are often no longer available for subsequent testing. The challenge to the informatics team is to add insight into approaches that can address where, in the continuum from flat-polished materials to 10-year clinical data, clinical performance can be accurately predicted.
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Summary |
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TOPAbstractIntroductionTissue EngineeringBiomaterialsSummaryReferences |
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Acknowledgments |
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Footnotes |
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References |
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TOPAbstractIntroductionTissue EngineeringBiomaterialsSummaryReferences |
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