Texture analysis of cone‐beam computed tomography images assists the detection of furcal lesion

Radiographic texture analysis of the hard tissue changes following socket preservation with allograft and xenograft materials for dental implantation: a randomized clinical trial

OBJECTIVES

This study aimed to assess the hard tissue changes following socket preservation with allograft and xenograft materials for dental implantation by texture analysis (TA) using cone-beam computed tomography (CBCT).

MATERIALS AND METHODS

This prospective clinical trial was conducted on 25 patients who required the extraction of carious mandibular posterior teeth and their subsequent replacement with dental implants. The patients were categorized into three groups: (I) no socket preservation, (II) socket preservation with xenograft material, and (III) socket preservation with allograft material. Four months after tooth extraction, the patients were recalled for preoperative assessment before dental implantation, and CBCT scans were obtained (Kvp:110, mA:1.94, S:3.6). MaZda software was used to compare homogeneity, contrast, and texture complexity on axial CBCT sections among the three groups.

RESULTS

Significant differences existed among the three groups in all parameters (P < 0.05) except for the mean correlation parameter (P > 0.05). The results showed no significant difference between the no graft and xenograft groups regarding contrast and differential (dif.) entropy (P > 0.05). Also, no significant difference was found between the xenograft and allograft groups regarding the dif. variance and also between the no graft and allograft groups regarding the inverse difference moment(InvDfMom) and dif. variance parameters (P > 0.05). All other pairwise comparisons revealed significant differences (P < 0.05).

CONCLUSION

TA can be used for the quantification of radiographic changes of bone following socket preservation and potentially accelerate the process of decision-making for dental implant treatment.

Differential diagnosis of cemento-osseous dysplasia and periapical cyst using texture analysis of CBCT

BACKGROUND

Radiolucencies found at the root apex in patients with cemento-osseous dysplasia (COD) may be mistaken for periapical cysts (PC) of endodontic origin. The purpose of this study was to examine the utility of quantitative texture analysis using cone-beam computed tomography (CBCT) to differentiate between COD and PC.

METHODS

Patients who underwent CBCT at Wonkwang University Daejeon Dental Hospital between January 2019 and December 2022 and were diagnosed with COD and PC by clinical, radiologic, and, if necessary, histopathologic examination were included. Twenty-five patients each were retrospectively enrolled in the COD and PC group. All lesions observed on axial CBCT images were manually segmented using the open-access software MaZda version 4.6 to establish the regions of interest, which were then subjected to texture analysis. Among the 279 texture features obtained, 10 texture features with the highest Fisher coefficients were selected. Statistical analysis was performed using the Mann-Whitney U-test, Welch's t-test, or Student's t-test. Texture features that showed significant differences were subjected to receiver operating characteristics (ROC) curve analysis to evaluate the differential diagnostic ability of COD and PC.

RESULTS

The COD group consisted of 22 men and 3 women, while the PC group consisted of 14 men and 11 women, showing a significant difference between the two groups in terms of sex (p=0.003). The 10 selected texture features belonged to the gray level co-occurrence matrix and included the sum of average, sum of entropy, entropy, and difference of entropy. All 10 selected texture features showed statistically significant differences (p<0.05) when comparing patients with COD (n=25) versus those with PC (n=25), osteolytic-stage COD (n=11) versus PC (n=25), and osteolytic-stage COD (n=11) versus cementoblastic-stage COD (n=14). ROC curve analysis to determine the ability to differentiate between COD and PC showed a high area under the curve ranging from 0.96 to 0.98.

CONCLUSION

Texture analysis of CBCT images has shown good diagnostic value in the differential diagnosis of COD and PC, which can help prevent unnecessary endodontic treatment, invasive biopsy, or surgical intervention associated with increased risk of infection.

Effect of the pulsed electromagnetic field in the repair of a calvaria critical bone defect in rats: cone beam computed tomographic and histomorphometric analysis.: PEMF in the repair of a calvaria critical bone defect: CBCT analyses

INTRODUCTION

The present study evaluated the effect of two protocols of Pulsed Electromagnetic Field (PEMF) therapy on bone neoformation on calvaria critical defects in rats.

MATERIAL & METHODS

96 rats were randomly divided into 3 groups: Control Group (CG; n=32); Test Group - PEMF 1 hour (TG1h; n=32) and Test Group - PEMF 3 hour (TG3h; n=32). A Critical-size Bone Defect (CSD) was surgically created in the calvaria of rats. The animals in the test groups were exposure to PEMF for 5 days a week. The animals were euthanized at 14, 21, 45 and 60 days. The specimens were processed for volume and texture (TAn) analysis, by Cone Beam Computed Tomography (CBCT) and histomorphometric analysis, RESULTS: Histomorphometric and volume analyses revealed that there was no statistically significant difference in the repair of bone defects between groups receiving PEMF therapy and CG. TAn revealed a statistically significant difference between the groups only for the entropy parameter, in which TG1h group presented a higher value compared to CG on 21 days. TG1h and TG3h did not accelerate bone repair in calvarial critical size defect and the parameters of PEMF should be considered.

DISCUSSION

This study showed that PEMF application on CSD in rats does not accelerate bone repair. Although literature showed a positive association in biostimulation on bone tissue with the parameters applied, studies with other PEMF parameters are essential to verify improving this study design.

Mechanical Properties, Fractal Dimension, and Texture Analysis of Selected 3D-Printed Resins Used in Dentistry That Underwent the Compression Test

Three-dimensional printing is finding increasing applications in today’s world. Due to the accuracy and the possibility of rapid production, the CAD/CAM (computer-aided design/computer-aided manufacturing) technology has become the most desired approach in the preparation of elements, especially in medicine and dentistry. This study aimed to compare the biomechanical properties, fractal dimension (FD), and texture of three selected materials used for 3D printing in dentistry. Three biomaterials used in 3D printing were evaluated. The materials were subjected to the compression test. Then, their mechanical features, FD, and texture were analyzed. All the tested materials showed different values for the studied properties. The only statistically insignificant difference was observed for the force used in the compression test. All three materials showed differences in width and height measurements. The difference in the decrease between the compression plates was also significant. For Dental LT Clear, the mean value was 0.098 mm (SD = 0.010), while for BioMed Amber it was 0.059 mm (SD = 0.019), and for IBT it was 0.356 mm (SD = 0.015). The nominal strain also differed between the materials. IBT had the highest mean value (7.98), while BioMed Amber had the smallest (1.31). FD analysis revealed that Dental LT Clear did not show differences in the structure of the material. The other two materials showed significant changes after the compression test. Texture analysis (TA) revealed similar results: BioMed Amber resin showed significantly less pronounced texture changes compared to the other two materials. BioMed Amber also showed the most stable mechanical properties, whereas those of IBT changed the most. Fractal analysis revealed that IBT showed significant differences from the other two materials, whereas TA showed that only Dental LT Clear did not show changes in its texture after the compression test. Before the compression, however, BioMed Amber differed the most when bone index was taken into account.

Magnetic resonance image texture analysis of the lateral pterygoid muscle in patients with rheumatoid arthritis: a preliminary report

OBJECTIVES

Magnetic resonance imaging (MRI) is useful for assessing temporomandibular disorders (TMDs). However, few studies have attempted texture analysis of the lateral pterygoid muscle in patients with rheumatoid arthritis (RA). This study aims to investigate the usefulness of MRI texture analysis of the lateral pterygoid muscle of patients with RA of the temporomandibular joint (TMJ).

METHODS

We analyzed the data from 36 patients (18 non-RA patients and 18 RA patients) who complained of pain and underwent MRI between April 2008 and August 2021. From the MRI scans of these patients, 279 radiomics features were extracted using STIR image data of the ROIs on the lateral pterygoid muscle of patients with RA and analyzed using MaZda ver. 3.3. Seven gray-level co-occurrence matrix features (Sum entropy, Sum variance) were picked up using the Fisher coefficient, for comparison between the RA and non-RA groups. Data analysis was performed using the Mann-Whitney U test A P value of < 0.05 was considered as statistically significant.

RESULTS

All seven lateral pterygoid muscle radiomic features indicated significant differences between the non-RA and RA groups (P < 0.05).

CONCLUSION

MRI texture analysis shows potential for application in radiomics diagnosis of RA in TMJ.

Magnetic resonance imaging texture analysis for quantitative evaluation of the mandibular condyle in juvenile idiopathic arthritis

OBJECTIVES

Juvenile idiopathic arthritis (JIA) is a chronic inflammatory disease that affects the joints and other organs, including the development of the former in a growing child. This study aimed to evaluate the feasibility of texture analysis (TA) based on magnetic resonance imaging (MRI) to provide biomarkers that serve to identify patients likely to progress to temporomandibular joint damage by associating JIA with age, gender and disease onset age.

METHODS

The radiological database was retrospectively reviewed. A total of 45 patients were first divided into control group (23) and JIA group (22). TA was performed using grey-level co-occurrence matrix (GLCM) parameters, in which 11 textural parameters were calculated using MaZda software. These 11 parameters were ranked based on the p value obtained with ANOVA and then correlated with age, gender and disease onset age.

RESULTS

Significant differences in texture parameters of condyle were demonstrated between JIA group and control group (p < 0.05). There was a progressive loss of uniformity in the grayscale pixels of MRI with an increasing age in JIA group.

CONCLUSIONS

MRI TA of the condyle can make it possible to detect the alterations in bone marrow of patients with JIA and promising tool which may help the image analysis.

Efficacy of magnetic resonance imaging texture features of the lateral pterygoid muscle in distinguishing rheumatoid arthritis and osteoarthritis of the temporomandibular joint

OBJECTIVES

The aim of this study was to assess whether magnetic resonance imaging (MRI) texture features of the lateral pterygoid muscle can distinguish between rheumatoid arthritis (RA) and osteoarthritis (OA) of the temporomandibular joint (TMJ).

METHODS

The authors extracted 279 texture features from 36 patients with RA and OA from the region of interest set for the lateral pterygoid muscle on short tau inversion recovery (STIR) images using MaZda Ver.3.3. A total of 10 texture features were selected using Fisher's coefficients, as well as probability of error and average correlation coefficients. Data observed to have a non-normal distribution using the Kolmogorov-Smirnov test were compared using the Mann-Whitney U-test. Receiver operating characteristic (ROC) curves were used to assess the ability of the 10 texture features to distinguish RA and OA of the TMJ.

RESULTS

A total of 10 features (5 Correlation, 3 Run Length Nonuniformity, 1 Sigma, and 1 Teta) were selected from 279 texture features. These texture features revealed significant differences between the RA and OA groups (p < 0.01). The sensitivity, specificity, accuracy, and area under the ROC curve of the texture features for distinguishing RA from OA were 0.78-0.94, 0.89-1.0, 0.86-0.92, and 0.89-0.95, respectively.

CONCLUSION

MRI texture analysis of the lateral pterygoid muscle may be useful for distinguishing between RA and OA of the TMJ.

Cone-beam computed tomography texture analysis can help differentiate odontogenic and non-odontogenic maxillary sinusitis

Purpose

This study aimed to assess texture analysis (TA) of cone-beam computed tomography (CBCT) images as a quantitative tool for the differential diagnosis of odontogenic and non-odontogenic maxillary sinusitis (OS and NOS, respectively).

Materials and Methods

CBCT images of 40 patients diagnosed with OS (N=20) and NOS (N=20) were evaluated. The gray level co-occurrence (GLCM) matrix parameters, and gray level run length matrix texture (GLRLM) parameters were extracted using manually placed regions of interest on lesion images. Seven texture parameters were calculated using GLCM and 4 parameters using GLRLM. The Mann-Whitney test was used for comparisons between the groups, and the Levene test was performed to confirm the homogeneity of variance (α=5%).

Results

The results showed statistically significant differences (P<0.05) between the OS and NOS patients regarding 3 TA parameters. NOS patients presented higher values for contrast, while OS patients presented higher values for correlation and inverse difference moment. Greater textural homogeneity was observed in the OS patients than in the NOS patients, with statistically significant differences in standard deviations between the groups for correlation, sum of squares, sum of entropy, and entropy.

Conclusion

TA enabled quantitative differentiation between OS and NOS on CBCT images by using the parameters of contrast, correlation, and inverse difference moment.

In vivo study of cone beam computed tomography texture analysis of mandibular condyle and its correlation with gender and age

OBJECTIVE

Texture analysis is an image processing method that aims to assess the distribution of gray-level intensity and spatial organization of the pixels in the image. The purpose of this study was to investigate whether the texture analysis applied to cone beam computed tomography (CBCT) images could detect variation in the condyle trabecular bone of individuals from different age groups and genders.

METHODS

The sample consisted of imaging exams from 63 individuals divided into three groups according to age groups of 03-13, 14-24 and 25-34. For texture analysis, the MaZda^® software was used to extract the following parameters: second angular momentum, contrast, correlation, sum of squares, inverse difference moment, sum entropy and entropy. Statistical analysis was performed using Mann-Whitney test for gender and Kruskal-Wallis test for age (P = 5%).

RESULTS

No statistically significant differences were found between age groups for any of the parameters. Males had lower values for the parameter correlation than those of females (P < 0.05).

CONCLUSION

Texture analysis proved to be useful to discriminate mandibular condyle trabecular bone between genders.

Risk assessment of external apical root resorption associated with orthodontic treatment using computed tomography texture analysis

OBJECTIVES

This study aimed to quantitatively assess maxillary central incisor roots using pre-orthodontics computed tomography (CT) texture analysis as part of a radiomics quantitative analysis.

METHODS

This retrospective case-control study included 16 patients with external apical root resorption (EARR) and 16 age- and sex-matched patients without EARR, after orthodontic treatment who underwent pre-orthodontics CT for jaw deformities. All patients were treated with a fixed orthodontic appliance before and after surgical orthodontic treatment. EARR was defined as root resorption ≥ 2 mm of the left and right maxillary central incisors on CT images more than 2 years after the start of orthodontic treatment. Texture features of the maxillary central incisor with and without EARR after orthodontic treatment were analyzed using the open-access software, MaZda Ver. 3.3. Ten texture features were selected using the Fisher method in MaZda from 279 original parameters, which were calculated for each of the maxillary central incisors with and without EARR. The results were tested using the Student's t test, Welch's t test, or Mann-Whitney U test.

RESULTS

Four gray-level run length matrix features and six gray-level co-occurrence matrix features displayed significant differences between both the groups (p < 0.01).

CONCLUSIONS

CT texture analysis was able to quantitatively assess maxillary central incisor roots and distinguish between maxillary central incisor roots with and without EARR. CT texture analysis may be a useful method for predicting EARR after orthodontic treatment.

Radiomics in bone pathology of the jaws

OBJECTIVE

To define which are and how the radiomics features of jawbone pathologies are extracted for diagnosis, predicting prognosis and therapeutic response.

METHODS

A comprehensive literature search was conducted using eight databases and gray literature. Two independent observers rated these articles according to exclusion and inclusion criteria. 23 papers were included to assess the radiomics features related to jawbone pathologies. Included studies were evaluated by using JBI Critical Appraisal Checklist for Analytical Cross-Sectional Studies.

RESULTS

Agnostic features were mined from periapical, dental panoramic radiographs, cone beam CT, CT and MRI images of six different jawbone alterations. The most frequent features mined were texture-, shape- and intensity-based features. Only 13 studies described the machine learning step, and the best results were obtained with Support Vector Machine and random forest classifier. For osteoporosis diagnosis and classification, filtering, shape-based and Tamura texture features showed the best performance. For temporomandibular joint pathology, gray-level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), Gray Level Size Zone Matrix (GLSZM), first-order statistics analysis and shape-based analysis showed the best results. Considering odontogenic and non-odontogenic cysts and tumors, contourlet and SPHARM features, first-order statistical features, GLRLM, GLCM had better indexes. For odontogenic cysts and granulomas, first-order statistical analysis showed better classification results.

CONCLUSIONS

GLCM was the most frequent feature, followed by first-order statistics, and GLRLM features. No study reported predicting response, prognosis or therapeutic response, but instead diseases diagnosis or classification. Although the lack of standardization in the radiomics workflow of the included studies, texture analysis showed potential to contribute to radiologists' reports, decreasing the subjectivity and leading to personalized healthcare.

Magnetic resonance imaging texture analysis in the quantitative evaluation of acute osteomyelitis of the mandibular bone

OBJECTIVES

Accurate assessment of radiological images can help in early diagnosis and therapy of suppurative osteomyelitis (OM). The purpose of this study was to apply texture analysis to MRI as a means of quantitatively evaluating acute OM of the mandible.

METHODS

We analyzed the data from 38 patients who complained of pain and underwent MRI between April 2017 and March 2019. From the MRIs of these patients, with (n = 19) and without OM (n = 19), 279 radiomics features were extracted using short tau inversion recovery, data of the regions of interest and analyzed with MaZda v. 3.3. 10 features, including one histogram feature (90th percentile), eight gray-level co-occurrence matrix features (Sum Averg), and one gray-level run-length matrix feature (Horzl_RLNonUni), were selected using Fisher coefficient and compared between the acute OM and non-OM groups. The two groups were compared using Mann-Whitney U test with p value set at 0.05.

RESULTS

All 10 radiomics features showed significant differences between the acute OM and non-OM groups (p < 0.05).

CONCLUSIONS

MRI texture analysis has potential application in radiomics diagnosis of acute OM of the mandible.

Application of Texture and Fractal Dimension Analysis to Evaluate Subgingival Cement Surfaces in Terms of Biocompatibility

Biocompatibility is defined as “the ability of a biomaterial, prosthesis, or medical device to perform with an appropriate host response in a specific application”. Biocompatibility is especially important for restorative dentists as they use materials that remain in close contact with living tissues for a long time. The research material involves six types of cement used frequently in the subgingival region: Ketac Fil Plus (3M ESPE, Germany), Riva Self Cure (SDI, Australia) (Glass Ionomer Cements), Breeze (Pentron Clinical, USA) (Resin-based Cement), Adhesor Carbofine (Pentron, Czech Republic), Harvard Polycarboxylat Cement (Harvard Dental, Great Britain) (Zinc polycarboxylate types of cement) and Agatos S (Chema-Elektromet, Poland) (Zinc Phosphate Cement). Texture and fractal dimension analysis was applied. An evaluation of cytotoxicity and cell adhesion was carried out. The fractal dimension of Breeze (Pentron Clinical, USA) differed in each of the tested types of cement. Adhesor Carbofine (Pentron, Czech Republic) cytotoxicity was rated 4 on a 0–4 scale. The Ketac Fil Plus (3M ESPE, Germany) and Riva Self Cure (SDI, Australia) cements showed the most favorable conditions for the adhesion of fibroblasts, despite statistically significant differences in the fractal dimension of their surfaces.

Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology

OBJECTIVES

The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS).

METHODS

Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann-Whitney U test.

RESULTS

Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients.

CONCLUSIONS

CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices.

Texture analysis of cone beam computed tomography images reveals dental implant stability

The aim of this study was to characterize the alveolar bone of edentulous maxillary sites using texture analysis (TA) of cone beam computed tomography (CBCT) images and to correlate the results to the insertion torque, thus verifying whether TA is a predictive tool of final implant treatment. This study was conducted on patients who had received single implants in the maxilla (46 implants) 1year earlier and whose torque values were properly recorded. Three cross-sections of the sites were selected on CBCT scans. Two regions of interest (ROIs) corresponding to the implant bone site and peri-implant bone were also outlined, according to virtual planning. The CBCT scans were exported to MaZda software, where the two ROIs were delimited following the previously demarcated contours. Values for the co-occurrence matrix were calculated for TA. With regard to the insertion torque value, there was a direct correlation with the contrast of the peri-implant bone (P<0.001) and an inverse correlation with the entropy of the implant bone site (P=0.006). A greater contrast indicates a greater torque value for insertion of the implants, and there is a possible association with a lower entropy value of the implant-bone interface.

Differentiation of periapical granuloma from radicular cyst using cone beam computed tomography images texture analysis

Objective

This study aimed to investigate the use of texture analysis for characterization of radicular cysts and periapical granulomas and to assess its efficacy to differentiate between both lesions with histological diagnosis.

Methods

Cone beam computed tomography (CBCT) images were obtained from 19 patients with 25 periapical lesions (14 radicular cysts and 11 periapical granulomas) confirmed by biopsy. Regions of interest were created in the lesions from which 11 texture parameters were calculated. Spearman's correlation analysis was performed and adjusted with Benjamini-Hochberg false discovery rate procedure (FDR <0.005).

Results

The texture parameters used to differentiate the lesions were assessed by using a receiver operating characteristic analysis. Five texture parameters were predictive of lesion differentiation for eight positions: angular second moment; sum of squares; sum of average; contrast; correlation.

Conclusion

Texture analysis of CBCT scans distinguishes radicular cysts from periapical granulomas and can be a promising diagnostic tool for periapical lesions.

Clinical significance

Texture analysis can be used in diagnostic and treatment monitoring to provide supplementary information.