Fractal texture analysis of the healing process after bone loss

Degenerative Temporomandibular Disorders: An Assessment of Bone Trabecular Structure Using Fractal Analysis in Digital Panoramic Radiographs

Introduction Fractal analysis has proved to be a salient tool to quantitatively assess the qualitative changes in the bone trabeculae of patients with hyperparathyroidism, osteoporosis, and various temporomandibular disorders, including osteoarthritis (OA) and rheumatoid arthritis of temporomandibular joint (TMJ), in several previous studies. The purpose of this study was to use fractal analysis to assess alterations in the trabecular pattern of the mandibular condyle in patients with degenerative temporomandibular disorders. Materials and methods This study comprised 98 subjects with 49 subjects in the study group and 49 subjects in the control group, aged 18-50 years. Age and sex in the control group were matched to those in the case group. The subjects were assessed clinically with the Diagnostic Criteria for Temporomandibular Disorders. Digital panoramic X-ray equipment with set parameters of 70 kvp, 8 mA, and 16-second exposure duration was used to take panoramic radiographs. Fractal analysis was done and the calculated fractal dimension value was obtained using ImageJ version 1.48 software (National Institutes of Health, Bethesda, MD). The same observer used Muir and Goss's method to rate the total degenerative changes in the condylar surfaces, which were substantiated by the calculated fractal dimension value. The data were statistically analyzed. Results The results revealed a significant difference (p-value = 0.041) between the mean fractal value in the case group's (1.35) and the control group's (1.38) left sides whereas the differences in the mean fractal values between the case and control groups on the right side was not significant (p-value = 0.49). Conclusion It is recommended to use the fractal dimension value and the total degenerative severity score together to quantify degenerative changes in the TMJ OA rather than exclusively relying on fractal value.

Multifractal approach for a biological porous media: Human dentin case

A multifractal characterization to human dentin porosity is made. Micrographs of human dentin samples gotten from scanning electron microscopy (SEM) were studied in order to characterize porosity. We got the generalized dimensions (multifractal moments)D q for pore space and matrix skeleton on gray scale and binary images for samples of both gender. For the case, we found that superficial porosityη s is linked to mass fractal dimensionD 0 in an approximately linear relationship asD 0 ≈ η s + d ¯ for binary images. In addition, probability density distribution (PDD) for pore diameters is found a normal PDD type. Other quantities of interest like mean, standard deviation, maximum and minimum pore diameters, voit ratios, and percentage of chemical composition are reported. RESEARCH HIGHLIGHTS: SEM sample, images and procedure for multifractal analysis are detailed. Micro patterns in grayscale are multifractal and in binary scale are monofractals. Superficial porosity is relate to mass fractal dimension approximately linearly. From the porosity values, voit ratios are determined. Pores diameters obey a normal PDD.

Exploring the Importance of Corticalization Occurring in Alveolar Bone Surrounding a Dental Implant

Several measures describing the transformation of trabecular bone to cortical bone on the basis of analysis of intraoral radiographs are known (including bone index or corticalization index, CI). At the same time, it has been noted that after functional loading of dental implants such transformations occur in the bone directly adjacent to the fixture. Intuitively, it seems that this is a process conducive to the long-term maintenance of dental implants and certainly necessary when immediate loading is applied. The authors examined the relationship of implant design features to marginal bone loss (MBL) and the intensity of corticalization over a 10-year period of functional loading. This study is a general description of the phenomenon of peri-implant bone corticalization and an attempt to interpret this phenomenon to achieve success of implant treatment in the long term. Corticalization significantly increased over the first 5-year functional loading (CI from 200 ± 146 initially to 282 ± 182, p < 0.001) and maintained a high level (CI = 261 ± 168) in the 10-year study relative to the reference bone (149 ± 178). MBL significantly increased throughout the follow-up period—5 years: 0.83 ± 1.26 mm (p < 0.001), 10 years: 1.48 ± 2.01 mm (p < 0.001). MBL and radiographic bone structure (CI) were evaluated in relation to intraosseous implant design features and prosthetic work performed. In the scope of the study, it can be concluded that the phenomenon of peri-implant jawbone corticalization seems an unfavorable condition for the future fate of bone-anchored implants, but it requires further research to fully explain the significance of this phenomenon.

Measures of Corticalization

After the insertion of dental implants into living bone, the condition of the peri-implant bone changes with time. Implant-loading phenomena can induce bone remodeling in the form of the corticalization of the trabecular bone. The aim of this study was to see how bone index (BI) values behave in areas of bone loss (radiographically translucent non-trabecular areas) and to propose other indices specifically dedicated to detecting corticalization in living bone. Eight measures of corticalization in clinical standardized intraoral radiographs were studied: mean optical density, entropy, differential entropy, long-run emphasis moment, BI, corticalization index ver. 1 and ver. 2 (CI v.1, CI v.2) and corticalization factor (CF). The analysis was conducted on 40 cortical bone image samples, 40 cancellous bone samples and 40 soft tissue samples. It was found that each measure distinguishes corticalization significantly (p < 0.001), but only CI v.1 and CI v.2 do so selectively. CF or the inverse of BI can serve as a measure of peri-implant bone corticalization. However, better measures are CIs as they are dedicated to detecting this phenomenon and allowing clear clinical deduction.

Differential Diagnosis of Cysts and Granulomas Supported by Texture Analysis of Intraoral Radiographs

The aim of this study was to evaluate whether textural analysis could differentiate between the two common types of lytic lesions imaged with use of radiography. Sixty-two patients were enrolled in the study with intraoral radiograph images and a histological reference study. Full textural analysis was performed using MaZda software. For over 10,000 features, logistic regression models were applied. Fragments containing lesion edges were characterized by significant correlation of structural information. Although the input images were stored using lossy compression and their scale was not preserved, the obtained results confirmed the possibility of distinguishing between cysts and granulomas with use of textural analysis of intraoral radiographs. It was shown that the important information distinguishing the aforementioned types of lesions is located at the edges and not within the lesion.

Texture Analysis and its Applications in Biomedical Imaging: A Survey

Texture analysis describes a variety of image analysis techniques that quantify the variation in intensity and pattern. This paper provides an overview of several texture analysis approaches addressing the rationale supporting them, their advantages, drawbacks, and applications. This surveys emphasis is in collecting and categorising over five decades of active research on texture analysis. Brief descriptions of different approaches are presented along with application examples. From a broad range of texture analysis applications, this surveys final focus is on biomedical image analysis. An up-to-date list of biological tissues and organs in which disorders produce texture changes that may be used to spot disease onset and progression is provided. Finally, the role of texture analysis methods as biomarkers of disease is summarised.

The use of digital texture image analysis in determining the masticatory efficiency outcome

The mixture level of gum samples consisting of two colours can be assessed visually, using the electronic colorimetric method, employing digital image processing techniques and specially designed software. The study investigates the possibility of an alternative method called "digital texture image analysis" (DTIA) to assess improvement of masticatory efficiency in denture wearers. The objectives were i) to evaluate whether DTIA discriminates changes in the colour mixing ability within a group over time; ii) to determine whether DTIA can be used to detect improvement in chewing ability; iii) to select the most appropriate DTIA feature that sufficiently describes masticatory efficiency in CDs wearers. The study was designed as an intra-individual evaluation of masticatory efficiency, which was assessed in participants with new dentures in three follow-up times. A set of four texture features was used in the current study. Uniformity, Contrast, Homogeneity and Entropy of the obtained chewing-gum samples were correlated to the degree of gum comminution. A statistically significant difference in masticatory efficiency was observed based on the values of the analysed DTIA variables of gum samples-Uniformity, Contrast, Homogeneity, and Entropy-have changed in the participants during the observation period. The improvement of the masticatory function in relation to the mixing ability of two-coloured chewing gum could be traced by monitoring changes in the values of DTIA variables. The most increasement of masticatory efficiency was observed by monitoring DTIA parameters such as contrast, and homogeneity.

Use of fractal analysis in dental images: a systematic review

OBJECTIVES

This study reviewed the use of fractal analysis (FA) in dental images.

METHODS

A search was performed using PubMed, MEDLINE, LILACS, Web of Science and SCOPUS databases. The inclusion criteria were human studies in the English language, with no date restriction.

RESULTS

78 articles were found in which FA was applied to panoramic radiographs (34), periapical radiographs (21), bitewing radiographs (4), cephalometric radiograph (1), cone beam CT (15), micro-CT (3), sialography (2), and ultrasound (2). Low bone mineral density (21) and systemic or local diseases (22) around the bone of dental implants were the main subjects of the study of FA. Various sizes and sites of the regions of interest were used to evaluate the bone structure. Different ways were used to treat the image and to calculate FA. FA of 43 articles showed significant differences in the comparison of groups, mainly between healthy and sick patients.

CONCLUSIONS

FA in Dentistry has been widely applied to the study of images. Panoramic and periapical radiographs were those most frequently used. The Image J software and the box-counting method were extensively adopted in the studies reviewed herein. Further studies are encouraged to improve clarification of the parameters that directly influence FA.

Use of Texture Feature Maps for the Refinement of Information Derived from Digital Intraoral Radiographs of Lytic and Sclerotic Lesions

The aim of this study was to examine whether additional digital intraoral radiography (DIR) image preprocessing based on textural description methods improves the recognition and differentiation of periapical lesions. (1) DIR image analysis protocols incorporating clustering with the k-means approach (CLU), texture features derived from co-occurrence matrices, first-order features (FOF), gray-tone difference matrices, run-length matrices (RLM), and local binary patterns, were used to transform DIR images derived from 161 input images into textural feature maps. These maps were used to determine the capacity of the DIR representation technique to yield information about the shape of a structure, its pattern, and adequate tissue contrast. The effectiveness of the textural feature maps with regard to detection of lesions was revealed by two radiologists independently with consecutive interrater agreement. (2) High sensitivity and specificity in the recognition of radiological features of lytic lesions, i.e., radiodensity, border definition, and tissue contrast, was accomplished by CLU, FOF energy, and RLM. Detection of sclerotic lesions was refined with the use of RLM. FOF texture contributed substantially to the high sensitivity of diagnosis of sclerotic lesions. (3) Specific DIR texture-based methods markedly increased the sensitivity of the DIR technique. Therefore, application of textural feature mapping constitutes a promising diagnostic tool for improving recognition of dimension and possibly internal structure of the periapical lesions.

Comparison between fractal analysis and radiopacity evaluation as a tool for studying repair of an osseous defect in an animal model using biomaterials

OBJECTIVES

To evaluate bone repair of an osseous defect in a rat animal model through fractal analysis and radiopacity analysis in radiographic images.

METHODS

120 rats were subjected to extraction of their first molar and divided into four groups (n = 6/group) according to the material used for bone grafting: mineralized bovine bone, demineralized bovine bone (DBB), blood clot (BC - control) or Bio-Oss^® (BO). The animals were sacrificed after 1, 7, 14, 21 and 49 days and subjected to radiographic evaluation. For fractal analysis (FA), a square regionof interest of 30 × 30 pixels was used, and radiopacity was measured as the mean gray scale (MGS) value for three points of 5 × 5 pixels in the apical, medial and coronal regions of the defect. Histomorphometric evaluation was realized as the gold standard for bone neo-formation and maturation of the new osseous matrix.

RESULTS

Histomorphometric evaluation suggested that DBB showed faster mineralized deposition and resulted in more mature bone at the final time point of evaluation. Mineralized bovine bone and Bio-Oss presented similar results. The mineralized groups did not show significant differences in bone maturation. The radiopacity analysis revealed a significant difference (p < 0.05) between the DBB and blood clot groups at the final time point. FA did not show any significant differences at the final time point.

CONCLUSIONS

Mean gray scale seemed to be more effective for the quantification of bone repair than FA in the demineralized group in this animal model. Results for the mineralized groups did not reveal a significant difference, leading to the conclusion that both methods are effective.

Caries detection enhancement using texture feature maps of intraoral radiographs

Objectives

Dental caries are caused by tooth demineralization due to bacterial plaque formation. However, the resulting lesions are often discrete and thus barely recognizable in intraoral radiography images. Therefore, more advanced detection techniques are in great demand among dentists and radiographers. This study was performed to evaluate the performance of texture feature maps in the recognition of discrete demineralization related to caries plaque formation.

Methods

Digital intraoral radiology image analysis protocols incorporating first-order features (FOF), co-occurrence matrices, gray tone difference matrices, run-length matrices (RLM), local binary patterns (LBP), and k-means clustering (CLU) were used to transform the digital intraoral radiology images of 10 patients with confirmed caries, which were retrospectively reviewed in a dental clinic. The performance of the resulting texture feature maps was compared with that of radiographic images by radiologists and dental specialists.

Results

Significantly improved detection of caries spots was achieved by employing the CLU and FOF texture feature maps. The caries-affected area with sharp margins was well defined using the CLU approach. A pseudo-three-dimensional effect was observed in outlining the demineralization zones inside the cavity with the FOF 5 protocol. In contrast, the LBP and RLM techniques produced less satisfactory results with unsharp edges and less detailed depiction of the lesions.

Conclusions

This study illustrated the applicability of texture feature maps to the recognition of demineralized spots on the tooth surface debilitated by caries and identified the best performing techniques.