Diana Lorena Garcia Lopes

This study aimed to evaluate the effectiveness of two intracanal medications in promoting periapical bone healing following endodontic treatment using radiomics-enabled texture analysis of cone-beam computed tomography (CBCT) images as a novel biosensing technique. By quantifying tissue changes through advanced image analysis, this approach seeks to enhance the monitoring and assessment of endodontic treatment outcomes. Thirty-four single-rooted teeth with pulp necrosis and periapical lesions were allocated to two groups (17 each): calcium hydroxide +2% chlorhexidine gel (CHX) and Ultracal XS^®. CBCT scans were obtained immediately after treatment and three months later. Texture analysis performed using MaZda software extracted 11 parameters based on the gray level co-occurrence matrix (GLCM) across two inter-pixel distances and four directions. Statistical analysis revealed significant differences between medications for S [0,1] inverse difference moment (p = 0.043), S [0,2] difference of variance (p = 0.014), and S [0,2] difference of entropy (p = 0.004). CHX treatment resulted in a more organized bone tissue structure post-treatment, evidenced by reduced entropy and variance parameters, while Ultracal exhibited less homogeneity, indicative of fibrous or immature tissue formation. These findings demonstrate the superior efficacy of CHX in promoting bone healing and underscore the potential of texture analysis as a powerful tool for assessing CBCT images in endodontic research.

This study aims to compare computed tomography (CT) with magnetic resonance imaging (MRI) of the temporomandibular joint (TMJ) by using texture analysis (TA) to detect condylar bone marrow changes associated with the flattening and erosion of cortical bone. A total of 47 patients from the Dentomaxillofacial Radiology Division at São Paulo State University were evaluated. Images from 250 CT and 250 MRI images were assessed by experienced radiologists employing OnDemand3D software. Texture parameters were extracted with MaZda software (version 4.6), and we focused on regions of interest within the condyles. Statistical analysis revealed significant differences in texture parameters between the affected and control groups. CT images showed higher correlation values in cases of flattening, whereas MRI images demonstrated substantial changes in texture parameters for both flattening and erosion. These findings suggest that the texture analysis of CT and MRI images can effectively detect early and advanced degenerative changes in the TMJ, thus providing valuable insights into the underlying pathophysiology and aiding in early intervention and treatment planning.

This study explores the efficacy of texture analysis by using preoperative multi-slice spiral computed tomography (MSCT) to non-invasively determine the grade of cellular differentiation in head and neck squamous cell carcinoma (HNSCC). In a retrospective study, MSCT scans of patients with HNSCC were analyzed and classified based on its histological grade as moderately differentiated, well-differentiated, or poorly differentiated. The location of the tumor was categorized as either in the bone or in soft tissues. Segmentation of the lesion areas was conducted, followed by texture analysis. Eleven GLCM parameters across five different distances were calculated. Median values and correlations of texture parameters were examined in relation to tumor differentiation grade by using Spearman’s correlation coefficient and Kruskal–Wallis and Dunn tests. Forty-six patients were included, predominantly female (87%), with a mean age of 66.7 years. Texture analysis revealed significant parameter correlations with histopathological grades of tumor differentiation. The study identified no significant age correlation with tumor differentiation, which underscores the potential of texture analysis as an age-independent biomarker. The strong correlations between texture parameters and histopathological grades support the integration of this technique into the clinical decision-making process.