Multifractal characterization of healing process after bone loss. (July 2019)

• Record Type: Journal Article
• Authors: Borowska, Marta; Bębas, Ewelina; Szarmach, Janusz; Oczeretko, Edward
• Is Part Of: Biomedical signal processing and control. Volume 52(2019)
• Page Start: 179
• Page End: 186
• Publication Date: 2019-07
• Subjects: Multifractal analysis -- Fractal dimension -- Guided bone regeneration -- Xenografts -- Radiographic images; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2019.04.014
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: We describe the surfaces of radiovisiograms in the healing process after bone loss using multifractal texture analysis. Radiovisiogams are an alternative technique for assessing the structure of bone remodeling. The studied group consists of 19 patients: Group A – images directly after the procedure, Group B – images after 12 months. The multifractal spectrum width increases significantly one year after the operation. The multifractal analysis of the healing process after bone loss quantify a lasting clinical result. Abstract: Objective: In this work we have proposed to use multifractal analysis to evaluate the effectiveness of the healing process in postresectal and postcystal bone loss using the guided bone regeneration (GBR). Methods: The material of the study consists of 19 radiographic images obtained from patients (13 females and 6 males), observed within 1-year-long period, who had undergone bone augmentation with xenogenic material. Using radiographic images (RVG) made with digital radiography set Kodak RVG 6100 on the day of the procedure (Group A) and 12 months later (Group B), the degree of reconstruction of intraosseous defects were compared. A visual subjective evaluation of the healing process based on RVG images may not be sufficient. For this purpose, modern computer image analysis methods can be used. Pre-processing of radiographic images consisted of separating areas of interest (ROI) and binarization. The resulting images were analyzed using multifractals. The properties of biological structures cannot be sufficiently described in the Euclidean space, but they can be characterized by a parameter called the fractal dimension. Results: Significant increase (p < 0.0001) of multifractal features were found in patients from group B. Individual parameters may characterize bone structure, which had undergone bone augmentation with xenogenic material. Finally, we showed that the properly selected multifractal quantificators obtained for those images could be used to assign those images to the appropriate group. Conclusion: The proposed analysis based on RVG images could help to evaluate the healing process after bone loss. The analysis and interpretation of the healing process after bone loss using monofractal and multifractal analysis as a multi-steps process quantify a stable (good) clinical result.