Microstructural Evaluation of Dental Implant Success Using Micro-CT: A Comprehensive Review

Abstract

Micro-computed tomography (micro-CT) is an invaluable tool for the evaluation of dental implant success, whereby the assessment of bone microstructure is conducted. This review examines the role of micro-CT in evaluating bone microstructure in dental implants. A review of the current literature reveals that micro-CT enables the accurate measurement of bone volume, trabecular morphology, and connectivity density, all of which play a crucial role in implant stability. The high-resolution three-dimensional visualization capabilities of micro-CT are also beneficial for the analysis of osseointegration and the evaluation of bone augmentation biomaterials. Despite the existence of challenges such as imaging artifacts and limitations in in vivo applications, advancements in sub-micron resolution and artificial intelligence integration offer promise for improving diagnostic capabilities. Micro-CT provides valuable insights into bone microarchitecture and osseointegration dynamics, which have the potential to enhance pre-operative planning and clinical outcomes in dental implantology. Future research should prioritize the standardization of micro-CT analysis protocols and the exploration of direct clinical applications of this technology.

1. Introduction

The increasing predictability of dental implants has made them a viable therapy for replacing missing teeth [1]. In recent years, dental implants have been increasingly recognized as a revolutionary solution to this challenge, offering a more physiologic and long-term approach compared to conventional prosthetic methods [2,3]. The success and survival rates of single- and multiple-unit implant-supported implants do not differ significantly in the short and long term [4,5]. Howe et al. (2019) reported that the success rate of dental implant placement has been increasing. A recent study showed that the implant survival rate reached 96.4% after 10 years [6,7,8]. The long-term success of dental implants not only promises to restore chewing function but also has a significant impact on the aesthetics and quality of life of patients, but the most important thing to consider is the complexity of the interaction between the implant and the surrounding bone tissue, often referred to as osseointegration [9].

The long-term success of dental implants is contingent upon their stability within the oral cavity. This stability is critical for the functionality, aesthetics, and patient satisfaction of the dental implant [10]. Stable dental implants allow for effective mastication function and speech and maintain the integrity of the surrounding bone and soft tissue. The process of osseointegration is pivotal to achieving implant stability, which is contingent upon a robust bond between living bone and the implant surface [2,11,12]. The success of osseointegration is contingent upon a number of factors, including implant design, surface characteristics, surgical technique, and patient-related factors, such as the microstructure of the bone in which the implant is placed [2]. The stability of dental implants and their long-term success are directly correlated with the degree of osseointegration achieved [2,9,13].

In order to achieve successful treatment outcomes with an implant prosthesis, it is essential to undertake a series of evaluations at each stage of the process. These include model study evaluation, radiographic evaluation, and evaluations of both soft and hard tissues [14]. Once these evaluations have been completed, the next step is to select the most appropriate implant for the installation site. The use of diagnostic imaging has become an indispensable element in the planning and placement of dental implants, offering invaluable insights that enhance the predictability and success of the procedure. The recent advancements in imaging technology have markedly elevated the diagnostic precision, surgical planning, and clinical outcomes associated with dental implant placement [15].

Diagnostic imaging is employed to assess the patient’s condition for dental implants, specifically to evaluate the dimensions of the bone to be implanted, including its height, width, and shape. The type of implant to be utilized, the position of the remaining dentition, and the quality of the remaining bone will inform the selection of the radiological approach to be employed prior to implant surgery [16]. The use of cone beam computed tomography (CBCT) has become the preferred imaging modality for dental implant planning, offering three-dimensional (3D) visualization of anatomical structures with a reduced radiation dose [15]. A variety of imaging modalities are available, including tomography, computed tomography (CT), intraoral radiography, cone beam volumetric tomography, traditional extra-oral radiography, and magnetic resonance imaging [11]. It is of the utmost importance to select the most appropriate imaging modality for the patient’s condition and to ensure the accurate interpretation of the imaging results [16]. In order to assess bone morphology and microarchitecture, micro-CT is the recommended imaging technique for the evaluation of bone microstructure [17,18]. Micro-CT has the capacity to generate high-resolution three-dimensional images, thereby providing a novel perspective on the field of implantology research. This technology enables non-invasive visualization of bone structure at the sub-micron level, as well as precise quantitative analysis of various microstructural parameters that are critical to implant success [18,19,20]. The objective of this review is to provide a critical and comprehensive analysis of the existing literature on the use of micro-CT in the evaluation of bone microstructure for dental implant success.

2. Principles and Applications of Micro-CT in Dental Implant Evaluation

Micro-computed tomography (micro-CT) is an imaging technique that employs non-destructive X-rays to visualize the three-dimensional characteristics of a sample [20,21]. In dental implant placement, this technology can facilitate accurate assessment of bone morphology and implant placement. The use of micro-CT enables enhanced visualization of intricate anatomical structures, thereby optimizing implant placement and minimizing the incidence of surgical complications [19]. Furthermore, it facilitates the development of three-dimensional models, which can enhance pre-surgical planning processes [22]. In addition to being non-destructive, this technique also has a high resolution and good penetration depth, utilizing X-rays up to voxel sizes of 50–100 μm, which is at least a million times smaller than the voxels commonly used in medical imaging for humans [23].

Bohner et al. (2021) have conducted research to quantify trabecular bone using both CBCT and micro-CT. The objective was to compare the results obtained from measuring trabecular bone using CBCT and micro-CT. The null hypothesis of this study is that there is no difference in the size obtained in the test. In this study, the researchers employed two CBCT devices with disparate resolutions: the VV-Veraviewpocs R100 (Morita, Tokyo, Japan), where the field of view (FOV) was 4 × 4, the tube voltage was 75 kV, the tube current was 9 mA, and the voxel size was 0.125 µm. The second device was the Prexion-3D (Prexion, Tokyo, Japan), with an FOV of 5 × 5, a tube voltage of 90 kV, a tube current of 4 mA, and a voxel size of 0.125 µm. The CBCT device used had a scan time of 37 s and a voxel size of 108 µm. The micro-CT device employed was the SkyScan 1272 (Bruker, Billerica, MA, USA), with settings of 80 kV, 125 mA, and a voxel size of 16 µm. However, null hypotheses were rejected since bone values were under or overestimated by CBCT. The resulting data are presented in the following

Table 1. Descriptive data of µCT and CBCT measurements. SD = standard deviation; 95% CI = 95% confidence interval; BV.TV = trabecular volume fraction; BS.BV = bone specific surface; Tb. Th = trabecular thickness; Tb. Sp = trabecular separation. Descriptive data were described as mean ± standard deviation and 95% confidence interval (95% CI).

		µCT			VV			PR
		Mean ± SD	95% CI		Mean ± SD	95% CI		Mean ± SD	95% CI
			Inferior	Superior		Inferior	Superior		Inferior	Superior
BV.TV
	G1	53.17 ± 12.5 *	46.13	60.21	45.37 ± 10.8 *	38.91	51.84	37.86 ± 9.1 *	32.45	43.27
	G2	33.51 ± 3.78 *	26.47	40.54	32.57 ± 5.20 *	26.10	39.03	36.55 ± 4.2 *	31.14	41.96
BS.BV
	G1	52.98 ± 12.4 *	43.19	62.78	20.05 ± 3.77 *	16.32	23.78	34.65 ± 5.7 *	30.02	39.28
	G2	72.03 ± 11.6 *	62.87	81.19	27.25 ± 5.15 *	23.76	30.74	27.44 ± 5.5 *	23.11	31.77
Tb. Th
	G1	0.06 ± 0.01 *	0.05	0.07	0.24 ± 0.03 *	0.22	0.26	0.15 ± 0.01 *	0.13	0.17
	G2	0.05 ± 0.01 *	0.04	0.06	0.19 ± 0.01 *	0.17	0.21	0.18 ± 0.02 *	0.17	0.20
Tb. Sp
	G1	0.08 ± 0.02 *	0.06	0.10	0.27 ± 0.08 *	0.21	0.33	0.19 ± 0.06 *	0.14	0.24
	G2	0.12 ± 0.02 *	0.11	0.14	0.29 ± 0.06 *	0.24	0.35	0.28 ± 0.07 *	0.23	0.33

* indicates statistical significant difference among scanners at p ≤ 0.05.

[24].

The fundamental principle of micro-CT is to obtain a series of radiographic images of a sample, which is rotated between an X-ray source and an X-ray detector. These images are then reconstructed into cross-sectional images using a reconstruction algorithm (Figure 1) [20,25]. The technique has been employed in biomedical research across a range of disciplines, including musculoskeletal, neurological, cardio-respiratory, gastrointestinal, and longitudinal studies. The combination of micro-CT with histology also permits the identification of histological structures and the generation of data sets for subsequent research [26]. In three-dimensional analysis, micro-CT can be employed for the estimation of density, the calculation of porosity, the assessment of structural thickness, and the execution of morphometric analysis [20,27].

More sophisticated devices employ magnifying instrument objectives to achieve enhanced magnification and resolution. In order to achieve optimal settings for a micro-CT scan, it is necessary to consider two key parameters: the spot size (SS) and the awaited pixel size (PS). These parameters determine the source distance (SD) and detector distance (DD), which, in turn, affect the overall performance of the scan. A reduction in the source and detector distances (SD and DD) allows for the attainment of higher photon counts, thereby reducing the overall time required for the process (Figure 2). More sophisticated devices employ microscope objectives to achieve enhanced magnification and resolution. It is essential that the settings fulfill the conditions set out in Equation (1) [29].

$$PS\ge SS\cdot {\displaystyle \frac{DD}{SD}}$$

(1)

While micro-CT offers the benefit of visualizing solid structures, such as bone, without the necessity for special preparation, it is not without limitations in terms of contrasting soft tissues. The use of contrast agents can facilitate the overcoming of these limitations; however, the specific choice of contrast agent is contingent upon the characteristics of the sample and the constraints associated with its utilization [30]. Micro-CT scanning can be a rapid alternative to other techniques, such as histology. However, the duration of the scan may vary depending on the specific scan parameters employed [31]. It is possible that this may affect the radiation dose, which must be considered with particular attention in longitudinal studies. Nevertheless, it is not believed that X-ray radiation causes damage to the specimen’s DNA. Nevertheless, the utilization of synchrotron tomography can circumvent this limitation, facilitating the generation of volumetric data sets with sub-micron resolution in a relatively short time frame [20]. Furthermore, micro-CT techniques are unable to accurately represent the original color of the sample. However, recent advancements have enabled the digitization of internal structures and natural surface colors [32,33]. Additionally, the dimensions of the structure are a significant consideration, as structures below a specified threshold are not discernible by micro-CT [27].

The long-term storage of micro-CT data is also a significant challenge due to the considerable data volume involved. In conclusion, micro-CT is a powerful imaging technique that offers the advantages of non-destructive capabilities, high speed, and high resolution. The combination of micro-CT with other imaging techniques may prove an effective means of overcoming any potential shortcomings [20].

In the field of dental implant assessment, micro-CT provides a range of substantial benefits over traditional imaging techniques, including the following [27,34,35,36,37]:

• Sub-micron resolution;
• Non-destructive analysis;
• Three-dimensional visualization;
• Accurate quantification;
• Bone–implant interface analysis;
• Integration with advanced analyses, such as finite element analysis (FEA).

3. Critical Bone Microstructure Parameters for Implant Success

The long-term success of dental implants is contingent upon their stability within the oral cavity [9]. Implant stability is a critical factor influencing the functionality, aesthetic appeal, and patient satisfaction associated with implant restorations. Stable dental implants facilitate effective mastication and speech while maintaining the integrity of the surrounding bone and soft tissue [38]. Osseointegration is defined as the process of creating a robust connection between the bone and the implant surface through the formation of new bone tissue. The success of osseointegration is contingent upon a number of factors, including the design of the implant, the characteristics of the surface, the surgical technique employed, and the characteristics of the bone in which the implant is placed (host factors) [9]. The use of micro-CT enables the evaluation of multiple bone microstructure parameters that are crucial for osseointegration and implant stability. These include bone volume fraction (BV/TV [%]), bone surface (BS/TV), trabecular bone (Tb. Th, Tb. N, Tb. Sp, and Tb. Pf), connectivity density (Conn. D [1/mm³]), structure model index (SMI), and degree of anisotropy (DA) [39,40,41].

Bone volume fraction (BV/TV) is defined as the ratio of bone volume (BV) to total volume (TV) and serves as a fundamental indicator of bone density [39]. The study conducted by Tian et al. (2021) demonstrated a positive correlation between the BV/TV, insertion torque value (ITV), and implant stability quotient (ISQ) values. These findings suggest that higher BV/TV is associated with enhanced implant stability, thereby establishing BV/TV as a potential indicator for predicting the success of dental implants [42]. The study demonstrated a significant correlation between bone density (measured in Hounsfield units) and implant ultimate stability. The findings indicated that denser bone resulted in superior stability outcomes, while increased BV/TV was associated with a higher percentage of newly formed bone, which directly impacted implant stability. Furthermore, bone density and cortical thickness were identified as crucial predictive parameters for selecting the optimal surgical technique and implant type to enhance stability [43,44,45].

The trabecular examination includes trabecular thickness (Tb. Th), trabecular separation (Tb. Sp.), trabecular number (Tb. N), and trabecular pattern factor (Tb. Pf). These three components provide an in-depth understanding of the bone architecture [39]. The correlation between Tb. Th measurements and the mechanical strength of bone is of paramount importance, as Tb. Th serves as a pivotal factor influencing bone microarchitecture, as well as the overall quality of bone. Empirical studies suggest that diminished Tb. Th is associated with an elevated risk of fractures and a reduction in the mechanical integrity of bone. Research indicates that a reduction in Tb. Th correlates with a diminished bone volume fraction and a decline in bio-mechanical properties, including Young’s modulus and toughness, thereby suggesting a compromise in bone strength [46].

Tb. N is a principal indicator of bone microarchitecture complexity and connectivity. A reduction in Tb. N with age has been demonstrated in numerous studies, indicating a potential for diminished bone strength and heightened fracture risk in older individuals [47,48]. Tb. N and other trabecular parameters exhibit variation across different skeletal sites and populations, reflecting the influence of factors such as activity levels, subsistence strategies, and loading patterns [49,50].

Tb. Sp is a measure employed in bone histomorphometry for the evaluation of the structure of trabecular (or spongy) bone. Trabecular bone constitutes the porous inner part of bones, which can be found at the ends of long bones and in the vertebrae [51]. An increase in porosity results in a greater number of voids and a reduction in solid bone material. Tb. Sp is a measure of the distance between the trabeculae, which are the small rod-like structures within the spongy bone. As Tb. Sp increases, the bone becomes less dense and more porous. This results in a reduction of the bone material available to support and distribute mechanical loads, leading to a weakening of the bone and an increased risk of fractures. In conditions such as osteoporosis, increased trabecular separation is a common finding, indicating a reduction in bone strength and an increased risk of fracture [51,52,53].

Tb. Sp is a pivotal parameter in the evaluation of the microarchitecture of trabecular bone, which is especially pertinent in the context of dental implants. Tb. Sp is a measure of the distance between the trabeculae, which are the small rod-like structures that are characteristic of spongy bone. An elevated Tb. Sp value indicates an increased presence of voids or gaps within the bone, resulting in elevated bone porosity. This consequently leads to a reduction in the quantity of solid bone material available to support the implant. An augmented Tb. Sp value results in a less dense bone structure, which compromises its capacity to withstand mechanical loads. For dental implants, this is of paramount importance, as the implant necessitates a robust and stable foundation to function effectively [54].

From the observations with 3D imaging, the results showed an increase or positive correlation in implant stabilization on Tb. Th and Tb. N, while the Tb. Sp values decreased or correlated negatively with implant stability. This indicates that the smaller the gap between the trabeculae, the denser the bone conditions are, so it is possible that the bone bond to the implant is stronger [55].

BS/TV reflects the complexity of the bone surface in relation to the total volume, while connectivity density describes the degree of interconnection of trabecular structures per unit volume [39]. The in vivo study by Wang et al. (2021) testing a novel implant versus a control implant showed that an increase in BS/TV was positively correlated with increased time to new bone formation around the implant in both the novel and control implants [56]. There is a positive correlation between BV/TV and connectivity density. A denser bone volume will have a higher connectivity density value. This correlation is also similar to BS/TV. This result was obtained in a study by Bregoli et al. (2024) [57]. This correlation also has similarities to BS/TV [39].

The DA index is an index that describes the anisotropy orientation of the bone geometry with a value range of 0 to 1 (0 < DA < 1). A value of 0 indicates that the trabecular orientation is highly isotropic, and a value of 1 indicates that it is highly anisotropic [57]. The DA index is a commonly used measure of bone stiffness and strength [58]. Bregoli et al. (2024) found that there are significant differences between osteoporotic and non-osteoporotic bone. The results of osteoporotic bone have a trabecular structure in the longitudinal direction [57].

The SMI analysis is an index for the representation of the architecture of the trabecular bone in the form of plates or rods [59]. This index uses a range of values between 0 and 3 [60]. Zhang et al. (2020) noted that one of the causes of implant failure is marginal bone loss. In this condition, there is a very significant difference, one of which is characterized by an increase in the SMI value so that many plate shapes are visible or appear more regular in the trabecular structure in this area [61].

Tb. Pf represents a proxy measure of trabecular connectivity within a given region or volume of interest (VOI). The resulting measure value provides an illustration of bone connectivity. There is a close correlation between the change value of Tb. Pf and the SMI value with interpretation and relevance to the dental implant. This is typically associated with augmented bone strength and resilience, thereby suggesting superior support and enhanced osseointegration potential in the vicinity of the implant [41].

4. Evaluation of Bone Around Implants Using Micro-CT

Micro-computed tomography (micro-CT) is emerging as a valuable non-destructive 3D imaging modality for assessing bone–implant contact (BIC) and osseointegration. Studies have shown a strong correlation between micro-CT and traditional histomorphometry for BIC measurement [62,63]. Choi et al. (2019) compared the results of bone–implant contact examination with the use of 2D and 3D imaging. From the results obtained, no significant correlation was found between 3D and 2D BIC ratios. In addition, the standard deviation for BIC examination using 2D imaging was twice that of BIC examination using 3D imaging. This indicates a higher variability in 2D measurements [64].

The condition of the bone around the implant can be visualized using micro-CT [22]. Bone formation around implants occurs in two directions or involves two types of osteogeneses, namely distance osteogenesis and contact osteogenesis. In distance osteogenesis, bone forms from the host bone tissue toward the implant surface, and in contact osteogenesis, new bone forms from the implant surface toward the bone. The granulation process is followed by the formation of woven bone, which then transforms into more stable lamellar bone. This process increases bone contact with the implant and will contribute to the secondary stability of the implant [65].

The use of micro-CT allows for the observation and evaluation of all processes occurring during dental implant placement. This enables the rapid assessment of the implant and surrounding bone, facilitating informed decision-making. This method can be employed to quantify bone volume, bone surface area, trabecular thickness, trabecular number, trabecular separation, and bone-bonding ability. By utilizing this method, bone tissue in close proximity to the implant surface can be examined at a thickness of several microns, facilitating the evaluation of the implant osseointegration process in both quantitative and qualitative terms [22].

5. Correlation of Bone Microstructure with Implant Stability

One of the critical elements in the successful implementation of dental implant treatment is the identification of the most suitable site for prosthetic reconstruction and the subsequent planning of surgical procedures [66,67]. The condition of the bone that the implant will occupy also needs to be considered [67]. Recent research has demonstrated that the microarchitecture of trabeculae can impact the stability of dental implants, underscoring the importance of trabeculae assessment [24].

The success of a dental implantation procedure hinges on the attainment of adequate primary stability. The term primary stability refers to the implant’s inability to move after insertion. This depends on the mechanical bond between the implant and the surrounding bone. In the event of inadequate primary stability, excessive micro-movement may occur at the bone–implant interface during the process of bone healing. Secondary stability, in contrast, represents the biological stability that emerges as a consequence of alveolar bone formation and remodeling on the implant surface [24,43,68].

Implant stability can be quantified through the use of either invasive or non-invasive methodologies [13]. Invasive methods include removal torque (RT), histological, and histomorphometry studies; however, these methods are only employed in experimental settings. Non-invasive methods include percussion testing, X-ray analysis, the Periotest^®, and resonance frequency analysis (RFA). While some of these non-invasive techniques have inherent limitations, RFA is a valuable tool for assessing implant stability and is frequently employed in clinical settings. An additional crucial element influencing the efficacy of osseointegration is bone density, which can be assessed through computed tomography (CT) or cone beam CT (CBCT) [43]. In the context of preoperative measures, it is standard practice to perform a CT scan, in this case, a CBCT scan, in order to ascertain the quality of the bone in the region where the implant is to be placed [69].

In a retrospective study conducted by Raikar et al. (2017) on factors affecting implant success, it was stated that early implant failure can occur due to a failure in the osseointegration process that occurs within a few weeks to months post-implantation. This can be attributed to a number of factors, including bone necrosis, bacterial infection, surgical trauma, inadequate initial stability, and early occlusal loading, which can all contribute to early failure. Subsequent failures in the osseointegration process may result from prolonged and excessive mastication forces, which can lead to the development of peri-implantitis, a condition characterized by infection and bone loss around the implant. The available evidence indicates that implant failure is more prevalent with shorter and wider implants, largely due to the influence of poor bone density and operator skill. Nevertheless, shorter or wider implants may be suitable for unfavorable locations, such as those with lower bone density. In such cases, it is essential to consider not only the bone quality and quantity but also their impact on the success of dental implant placement [70].

Another factor that can contribute to implant instability is marginal bone loss, which should be taken into account following dental implant placement. Marginal bone loss is a multi-factorial event occurring in the cervical region of dental implants. These include implant malposition, excessive surgical trauma, high adhesion of supracrestal tissues, stress overload, micro-motion, location and bacterial infiltration of the implant-support connection, and periodontal phenotype. In addition, bone density and maintenance of oral hygiene are also important factors. Regardless of the underlying cause, marginal bone loss is a significant contributing factor to the development of peri-implantitis [71,72,73]. The current standards for acceptable implant success are defined as marginal bone loss (MBL) of less than 1.5–2.0 mm after the first year of functional loading, with subsequent loss of less than 0.2 mm per year. The variables were subjected to principal component analysis and correlation covariance matrices. All results pertinent to morphological variables were corroborated by a notable discrepancy and a reasonable degree of collinearity. The variables SMI, Tb. Pf, Tb. N, BS/BV, and BV/TV exhibited a stronger correlation with MBL than the remaining morphological variables, which did not contribute significantly to the model [61,72,74].

6. Micro-CT Application in Bone Quality Assessment

In general, the jawbone structure is composed of dense cortical bone and cancellous bone with a trabecular bone structure. As has been previously established, the quality of the jawbone is a critical determinant of the success of implant placement [75]. Micro-CT has emerged as a valuable tool for evaluating bone quality in dental implant planning and assessment. It offers high-resolution, non-destructive imaging of bone microarchitecture, facilitating comprehensive analysis of parameters such as bone density, porosity, and trabecular characteristics [23,76]. The utilization of micro-CT devices was initiated with the introduction of slice thicknesses in micrometers. Micro-CT exhibits excellent cross-sectional resolution, facilitating more comprehensive examination and enabling the scanning and construction of three-dimensional reconstructions of biological samples [22,76].

The use of micro-CT enables the classification of bone quality based on morphometric values, thus facilitating the development of personalized treatment plans and the evaluation of osseointegration [23,76]. Although the method is primarily used ex vivo, there is potential for in vivo applications, which could improve clinical decision-making in implantology. The quantitative approach of micro-CT enhances the precision and reliability of dental research. Researchers and clinicians can make evidence-based decisions regarding treatment strategies and patient management, relying on the quantifiable data provided by micro-CT [77].

The utilization of micro-CT in bone analysis can furnish a crucial scientific foundation for an array of experimental research designs pertaining to bone analysis [23]. It is anticipated that micro-CT will become an increasingly pivotal tool in advancing our comprehension of dental pathology, enhancing treatment efficacy, and, ultimately, optimizing patient care in the domain of dentistry [77].

7. Micro-CT in Biomaterial Evaluation and Bone Augmentation

In circumstances where bone damage has been incurred as a result of trauma or disease, a bone graft is typically employed as a replacement. The bone graft utilized is typically derived from the patient’s own bone tissue (autogenous) or can be procured from alternative sources, including bovine bone, allogenic bone, and hydroxyapatite. The use of autogenous bone is the optimal choice, but there are several disadvantages, including the necessity for additional surgical procedures, the risk of infection, and postoperative discomfort. Consequently, the use of allogenic and xenogeneic bone as bone substitutes is a prevalent practice [78].

The structural characterization of biomaterials is a crucial aspect in the investigation of the properties of bone substitutes prior to implantation and the selection of biomaterials for specific clinical applications. Porosity represents a crucial factor in the development of bone tissue engineering scaffolds, as it facilitates the invasion of progenitor cells. A high degree of porosity will facilitate the migration of mesenchymal and osteoblast cells to the recipient site. Pores between 100 and 300 µm are necessary to facilitate osteogenesis; however, larger pores may compromise the mechanical strength of the material. The results of preclinical micro-tomography analysis indicate that biomaterials derived from cattle and horses exhibit a greater resemblance to human bone than other materials [79].

The characteristics of porosity and pore size influence the surface area per volume. A high degree of porosity is conducive to the diffusion of nutrients, the transport of waste products, the formation of new blood vessels, and the growth of tissue. The control of porosity is of significance for all applications, given its impact on the mechanical properties of the material in question. The characterization of the microstructure is of great importance with regard to the performance of scaffolds. In this context, micro-CT represents a valuable instrument for the aforementioned purpose [80].

Zou et al. (2020) conducted research related to bone augmentation in dental implants. In this study, Zou examined three types of bone material utilized for augmentation: autogenous bone, allogenic bone, and artificial bone (bone substitute material). The micro-CT analysis conducted at weeks 4 and 12 yielded the following results: the bones derived from artificial bone exhibited higher values for BV/TV and bone mineral density (BMD) when compared to those derived from autogenous bone and allogenic bone. Furthermore, in Tb. Th, significant change was observed in the three groups. The Tb. N from the artificial bone group exhibited a significantly higher value compared to the autogenous and allogenic bone groups. With regard to Tb. Sp, the value of the artificial bone group was found to be relatively lower than that of the autogenous and allogenic bone groups. This suggests that the artificial bone group exhibits a more comprehensive repair process [81].

Recent studies have employed micro-CT analysis to evaluate various bone augmentation techniques. Kivovics et al. (2020) discovered a positive correlation between CBCT and micro-CT data, indicating the potential of CBCT for the analysis of bone microarchitecture in augmented sinuses [82]. In a recent study, Beitlitum et al. (2024) developed a novel volumetric micro-CT analysis to quantify new bone formation in rabbit calvarias. Their findings revealed a notable decline in bone formation from the outer to the inner regions across the grafting material [83]. In their 2020 study, Bedini and colleagues employed micro-CT to evaluate bone replacement scaffolds in human subjects. They analyzed morphological parameters, including porosity, bone volume fraction, and trabecular thickness, to assess biomaterial properties and their impact on bone regeneration [79]. These studies underscore the value of micro-CT in evaluating bone augmentation techniques and biomaterial efficacy.

8. Challenges and Limitations of Using Micro-CT in Dental Implant Evaluation

Micro-CT is a valuable tool in dental research, offering high-resolution 3D imaging without damaging the sample. It is employed in the fields of implantology, endodontics, and tissue engineering [22,28]. Nevertheless, the practical application of this approach is hindered by a number of limitations that impact its efficacy. These constraints include the potential for distortion of the resulting image due to artifacts in the imaging process [84,85]. The variability in imaging resolution affects the accuracy of the detection and measurement of gaps and the complexity of biological structures [86,87].

The direct utilization of micro-CT in clinical settings is currently quite restricted. As stated by Yu et al. (2022), the direct use of micro-CT in animals and humans is inherently dangerous due to the potential harm caused by the radiation produced [88]. Another disadvantage of micro-CT is the high cost, the necessity for extensive data storage, the inability to stain all objects for optimal contrast, the lengthy scanning and reconstruction process, and the need for expertise in operation [28,89]. To address the limitations of radiation dose and poor soft tissue contrast, researchers have developed strategies, including iterative reconstruction algorithms and novel contrast mechanisms such as spectral and phase contrast imaging [90]. The standardization of protocols and data analysis remains a significant challenge, as research findings from one system may not be directly applicable to another. Ethical considerations and radiation safety are also of paramount importance. The potential for long scan times is a further concern. Despite recent technological advances that have led to the development of low-dose micro-CT systems, concerns about radiation exposure remain [15,91]. Clark et al. (2021) presented several strategies to overcome these challenges, including improvements to contrast resolution, the utilization of advanced detector technology, the application of deep learning techniques, the adoption of phase contrast imaging, optimization of radiation dose, and enhancements to longitudinal imaging capabilities. By focusing on these strategies, researchers can effectively overcome the limitations associated with micro-CT imaging, thereby increasing its utility in preclinical research and translational applications [92].

9. Recent Innovations and Future Prospects

In recent times, there has been a proliferation of micro-CT systems, which now encompass a range of resolutions, from standard (~1 µm) to high (sub-micron) and ultra-high (below 0.6 µm). This diversification has significantly enhanced the capacity to visualize and analyze [34]. The application of high-resolution micro-CT enables a comprehensive understanding of the osseointegration dynamics, bone structure, and healing process, as well as the interaction between the bone microstructure and the implant surface [86]. The use of high-resolution imaging (sub-micron) enables the visualization of the bone–implant interface, facilitating the assessment of osseointegration and bone contact at a more detailed level [93]. Furthermore, high-resolution imaging techniques can discern a multitude of microstructural forms that influence osteoconductivity, including pore morphology and surface roughness, which are paramount for efficacious osseointegration [94].

The capacity to examine porous surfaces at the sub-micron level enables researchers to establish a correlation between the surface roughness of the implant and the biological response of the bone in the context of bonding [95]. The advancement of micro-CT imaging technology has enabled a comprehensive investigation of the osseointegration process of diverse materials and their combinations, leading to the development of implant designs that are more beneficial for patients than existing implant designs [96].

The incorporation of artificial intelligence (AI) into micro-CT data analysis for dental implantation will undoubtedly offer substantial advantages, including enhanced image resolution and more precise surgical planning. However, it is important to acknowledge the potential constraints associated with this technology, such as the possibility of inaccuracies and the necessity for high-quality data [97]. AI has the capacity to accurately segment complex anatomical features, such as the mandibular canal, thereby facilitating safer surgical planning and reducing the risk of injury. Furthermore, the implementation of this technology can also mitigate the incidence of human error and expedite the process while reducing costs [98,99].

The potential of AI in the field of dental implantology has recently been the subject of investigation. The findings indicated that the AI model demonstrated a high degree of accuracy in the recognition of implant types, with accuracy rates ranging from 93.8% to 98% when utilizing periapical and panoramic images. Furthermore, the AI model is capable of predicting implant success with an accuracy range of 62.4% to 80.5% [100]. A randomized controlled trial reported higher implant success rates and superior accuracy in AI-assisted planning in comparison to traditional methods. In dental implant planning using CBCT images, the AI algorithm achieved an overall accuracy of 96% for the lower jaw and 83% for the upper jaw in identifying areas of tooth loss. While the results of this study demonstrate promising potential, further research is necessary to enhance the accuracy, generalizability, and clinical applicability of AI-based approaches in implant dentistry [101].

Satapathy et al. (2024) showed the utilization of AI in the placement of dental implants has the potential to enhance the precision and efficacy of treatment planning in 20 patients. The results of this study demonstrated that treatment plans generated by AI exhibited a high degree of alignment with those devised by experienced clinicians, with an average discrepancy of less than 1 mm in implant position and two degrees in angulation. This demonstrates that AI is capable of providing highly accurate treatment plans. Furthermore, the AI-assisted planning process also reduces the time required, with an average time of only 10 min compared to 30 min for clinical planning. This efficiency can allow dental professionals to see more patients or allocate time to other important tasks (

Table 2. Comparison of implant positioning (in millimeters).

Patient	Clinical (x, y, z)	AI-Generated (x, y, z)	Deviation (x, y, z)
1	(12, 4, −3)	(11, 5, −2)	(1, 1, 1)
2	(9, 6, −2)	(10, 5, −3)	(1, 1, 1)
3	(11, 3, −4)	(11, 4, −4)	(0, 1, 0)
20	(10, 5, −3)	(10, 5, −3)	(0, 0, 0)
Mean	(10.5, 4.5, −3)	(10.5, 4.5, −3)	(0.5, 0.5, 0.5)
Std dev	(0.8, 0.6, 0.8)	(0.7, 0.6, 0.7)	(0.3, 0.2, 0.3)

,

Table 3. Comparison of implant angulation (in degrees).

Patient	Clinical Angulation	AI-Generated Angulation	Deviation
1	25	26	1
2	30	29	1
3	20	20	0
20	28	28	0
Mean	27.5	27.4	0.1
Std dev	3.2	2.9	0.2

and

Table 4. Comparison of implant depth (in millimeters).

Patient	Clinical Depth	AI-Generated Depth	Deviation
1	12	11	1
2	14	13	1
3	10	10	0
20	11	11	0
Mean	12.2	12.1	0.1
Std dev	1.3	1.2	0.1

). Additionally, the use of AI can enhance consistency in treatment planning, reducing discrepancies in approach that may arise from different clinicians. Consequently, AI can provide predictable outcomes and improve patient safety [102].

10. Clinical Implications and Recommendations

Micro-CT employs two principal scanning techniques, namely ex vivo and in vivo, which are applicable to a range of dental procedures. Ex vivo scans are employed for the analysis of extracted teeth or dental specimens, with the objective of understanding changes in bone density, porosity, and microstructure. The quantitative approach of micro-CT can enhance the precision of research, thereby facilitating evidence-based decision-making among clinicians with respect to treatment strategies and patient management. Micro-CT has a number of applications in the field of dentistry, including dental implantology and endodontics. It is anticipated that micro-CT will make a substantial contribution to enhancing comprehension of dental pathology, optimizing treatment outcomes, and benefiting patients in the field of dentistry [77].

The use of micro-CT in dentistry is pervasive, including applications such as dental implant placement and evaluation of treatment outcomes. Chaves et al. (2020) presented successful techniques for micro-CT analysis of dentoalveolar tissue in rodents, including optimal scanning parameters, a reproducible sample setup, segmentation and measurement of tissue volume, and interpretation of findings. It is imperative that standardized protocols for scanning and analysis related to the alveolar bone, as well as reporting of outcome data obtained through the use of micro-CT, be established in order to ensure the reproducibility and comparability of results across studies [103].

Computer-guided implant surgery provides the capacity to meticulously plan the positioning of implants in accordance with the intricacies of hard tissue anatomy, soft tissue volume, and the intended location of the prosthesis [104]. Nevertheless, errors and deviations can still occur, which may result in injury to anatomical structures or a mismatch between the prosthesis to be placed and the intended implant. Consequently, there is a continued clinical need for surgeons to utilize a guided implant system. A number of studies have addressed the factors that can result in a discrepancy between the planned implant position and the actual position achieved. Nevertheless, if process errors are avoided and potential deviations are minimized, accurate, stable, and durable results can be achieved. At present, micro-CT represents one of the solutions that can be employed to reduce the occurrence of failures in implant placement. The utilization of this instrument enables the acquisition of precise analytical data pertaining to the quality of bone and the process of osseointegration with dental implants [23]. In guided implant surgery, micro-CT plays an instrumental role in optimal implant planning and placement, thereby enhancing functional and aesthetic outcomes [104]. The further experience of surgeons in the utilization of this system, coupled with an understanding of potential process errors, is therefore necessary for this method to become a commonly employed standard of care [23,105].

11. Discussion

In the context of dental implants, micro-CT offers a number of advantages in the evaluation of the bone microstructure surrounding the implants. This is due to the technology’s capacity to assess a range of bone parameters, including bone volume, trabecular parameters, and other indicators [76]. Furthermore, this technique enables more precise three-dimensional visualization, facilitating the examination of the interaction between the implant and the surrounding tissue [105]. The utilization of micro-CT in dental implant research offers a means of gaining deeper insight into the osseointegration process and the prospective long-term success of the implant [22]. Additionally, micro-CT can be employed to monitor microstructural alterations over time. This provides valuable information about bone adaptation to the implant and potential complications that may arise [76]. The use of this technology also allows for the development of improved implants, with designs that can be customized based on the microstructural data obtained [106].

Micro-CT is a commonly used technique in bone biology research due to its ability to reveal details of the microarchitecture of the bone [40]. Micro-CT (µCT) is a medical imaging technique that uses X-rays to create 3D images of a sample [76]. In micro-CT, the sample is placed in the X-ray path, and projection images are obtained using a scintillator or another X-ray detector. The images produced by micro-CT are highly accurate and useful in bone biology research. Micro-CT can reveal details of bone microarchitecture, such as BV/TV, Tb. N, Tb. Th, and Tb. Sp. In addition, this technique can also be used to measure fractal dimension (FD), Tb. Pf, DA, and Conn. D as other parameters representing the complexity of the bone microarchitecture. Thus, micro-CT is essential for the quantitative assessment of bone microstructural parameters [40,107]. In marginal bone loss, The incorporation of micro-CT imaging for the assessment of SMI, Tb. Pf, and BV/TV prior to implant surgery has the potential to significantly enhance the prediction and management of potential MBL, thereby contributing to the long-term success of dental implant treatment. In order to effectively manage MBL in dental implant placement, it is imperative to gain an understanding of the role played by specific trabecular bone parameters. In particular, the SMI, Tb. Pf, and BV/TV should be considered. These parameters offer insight into the quality and quantity of microstructural bone around the implant [61].

The capacity of micro-CT imaging to achieve high contrast resolution in soft tissues is constrained. Nevertheless, the utilization of exogenous contrast agents and spectral CT techniques can facilitate the enhanced visibility of soft tissues. Furthermore, the utilization of photon-counting detectors (PCDs) enables dual-energy micro-CT scans, thereby facilitating the discrimination and differentiation of tissues and contrast agents. The incorporation of deep learning (DL) into micro-CT can facilitate further improvements in image quality and analysis, including the reduction of noise, the segmentation of images, and the correction of artifacts. The application of data-driven approaches and domain-specific knowledge can facilitate the expansion of micro-CT applications. X-ray phase contrast imaging (XPC) represents an alternative method that shows promise in its ability to detect density variations in soft tissues without the need for contrast agents, thus offering a potential avenue for in vivo imaging. The creation of sophisticated micro-CT scanners that prioritize a low radiation dose is also emphasized, as this enables repeated imaging of small animals in longitudinal studies while minimizing potential health risks [92].

It is anticipated that the advancement of low-dose reconstruction methodologies will prove beneficial in facilitating longitudinal imaging studies, particularly in the context of sensitive areas such as the coronary arteries in small animals. This will permit researchers to monitor disease progression over time without increasing the radiation doses that they administer. By focusing on this strategy, the researchers were able to overcome the limitations associated with using micro-CT, thereby increasing its usefulness in preclinical research and translational applications. Therefore, this micro-CT scanner with a low radiation dose represents a significant advancement for longitudinal studies in small animals [92].

Image quality is critical in the evaluation of musculoskeletal and dental pathology. Magnetic resonance imaging (MRI), radiography, ultrasonography, and computed tomography (CT) are commonly used modalities in this area. MRI has good soft tissue contrast, radiography is widely available, and CT is better at imaging changes in bone. Cone beam computed tomography (CBCT) imaging is useful in the detection of orthopedic pathology, dental pathology, joint trauma, and radiotherapy planning. CBCT has a low spatial resolution, so it can only see clinical features as small as 500 µm. This is not sufficient to observe changes in bone microstructure. Traditionally, bone microstructure can only be seen with micro-CT [108]. A micro-CT scan is the gold standard for the microstructure of the bones of a human or experimental animal [20].

Compared to CBCT scanning techniques, micro-CT has several advantages and disadvantages. The main advantage of micro-CT is its higher resolution, which allows for more detailed analysis, while the main disadvantages are the longer scan time and higher cost [20]. However, while cost and time are considerations, the benefits of more accurate analysis are often worth the investment, especially in the context of research and development of new implants [109]. In addition, the use of micro-CT can help understand the interaction between the implant and the surrounding tissue, which is important for improving clinical outcomes and reducing the risk of complications [110]. Therefore, the specific objectives of the research and the available resources should be considered when choosing between these two techniques.

A comparison of micro-CT, CBCT, and MRI in relation to dental implants is presented in the following table (

Table 5. Comparison between micro-CT, CBCT, and MRI.

Imaging Technique	Resolution	Three-Dimensional Capabilities	Usability	Advantages	Disadvantages
Micro-CT	1–10 µm	Yes	Research and laboratory application	High resolution, detailed microstructure analysis, non-destructive	Time consuming, limited sample size, expensive
CBCT	0.1–0.3 mm	Yes	Clinical application (dentist, etc.)	Lower radiation dose than conventional CT, cost effective, quick scan time	Limited field of view, still involves ionizing radiation, affected by metal artifacts
MRI	0.1–1 mm	Yes	Clinical application (soft tissue, etc.)	Excellent soft tissue contrast, no ionizing radiation, detailed soft tissue imaging	Affected by metal artifacts, expensive, longer scan times

), which outlines the key differences between the three imaging modalities.

In terms of cost, the use of micro-CT requires a significant or expensive investment [111]. However, this investment can provide significant long-term benefits in terms of innovation in the use of micro-CT for dental implantation [112]. Therefore, it is important for researchers and developers to conduct a thorough analysis of the potential benefits that can be obtained from micro-CT before deciding which method to use [22]. In addition, collaboration between different disciplines can accelerate the process of development and application of micro-CT [113]. With the involvement of experts from engineering, biomedical, and clinical fields, it is expected that the solutions found will be more comprehensive and effective to meet the needs of patients [114]. In addition, a better understanding of the mechanism of action of micro-CT can open up new opportunities in the research and development of more biocompatible and efficient implant material [110].

In addition to the challenges associated with the storage of scanned data and the extended scan duration when utilizing micro-CT, the development of effective solutions to these issues is imperative. Potential solutions include the creation of more efficient data processing algorithms or the utilization of more sophisticated storage technologies, with the objective of reducing the time and cost associated with micro-CT [111]. Furthermore, enhancements to the network infrastructure are a crucial element in guaranteeing the rapid and secure transfer of data, thus facilitating more effective system integration in clinical practice through the utilization of micro-CT technology [115].

The integration of artificial intelligence with micro-CT has the potential to enhance diagnostic accuracy and surgical planning through the application of machine learning. Automated image analysis enables earlier detection and more accurate assessment of pathological conditions [116,117]. Therefore, collaboration between radiologists and data scientists is essential to optimize the use of this technology and ensure that the results obtained can be translated into effective clinical actions [118].

One potential avenue for exploration is the utilization of smartphone technology. In the current era, the advent of teledentistry has elevated the role of smartphones to that of a vital conduit for the dissemination of information to individuals in need of dental care. Pascadopoli et al. (2023) conducted a literature review on the utilization of smartphone applications in the prevention, management, and monitoring of diseases or abnormalities in the mouth, including both hard and soft tissue, as well as diagnostic radiological imaging [119]. The development of smartphone-based imaging has been carried out. The utilization of smartphones in biomedical imaging has been a topic of considerable discussion, with a number of factors identified as being of particular importance, including cost, portability, connectivity, ease of use, and scalability. However, in some cases, the advantages of biomedical imaging systems utilizing smartphones remain open to question [120].

Furthermore, ongoing training for medical personnel is necessary to ensure that they can make the most of this technology and understand the interpretation of results generated by artificial intelligence-based systems [121]. With the support of educational and research institutions, it is hoped that innovations in this field can continue to grow and provide significant benefits to patients.

12. Conclusions

Micro-CT is an advanced tool for assessing the success of dental implants, particularly through detailed three-dimensional imaging and quantitative analysis of bone quality and implant osseointegration. These capabilities facilitate more accurate decision-making by dentists in the planning and evaluation of treatment. Additionally, micro-CT plays a pivotal role in the research and development of new implants, providing a deeper understanding of the interaction between the implant and the surrounding tissue.

Although micro-CT is an extremely effective tool for ex vivo applications, its clinical use is constrained by factors such as time, cost, and the high radiation dose required. However, as technology advances and costs decline, the utilization of micro-CT is anticipated to expand within the domain of clinical practice. This will facilitate more precise evaluation and improved treatment for a larger number of patients. Further research is required to optimize imaging protocols and reduce radiation exposure, thereby ensuring patient safety without compromising image quality. Future studies will concentrate on overcoming the constraints of micro-CT for in vivo applications by developing low-radiation systems and miniaturized devices for human use. The incorporation of artificial intelligence has the potential to transform micro-CT by facilitating enhanced image processing, automated data analysis, enhanced diagnostics, and the reduction of human error.