Use and Evaluation of a Computer-Assisted Examination Method for the Diagnosis and Analysis of Medication-Related Osteonecrosis of the Jaw

Overview

Journal Craniomaxillofac Trauma Reconstr

Publisher Sage Publications

Date 2021 Feb 22

PMID 33613834

Citations 1

Authors

Max Wilkat

Daman Deep Singh

Isabelle Lutz

Henriette Mollmann

Nils-Claudius Gellrich

Majeed Rana

Affiliations

Soon will be listed here.

Abstract

The aim of the present study was to analyze the size of the preoperatively calculated defect volume of MRONJ patients (medication-related osteonecrosis of the jaw) and to develop a computer-aided tool based on techniques of AI (artificial intelligence) that facilitates diagnostics of MRONJ. For this purpose, on the basis of 3D (three-dimensional) data sets of 175 MRONJ patients, the outline of the necrosis was marked with the software iPlan 3.0.5 (BrainLAB AG) thus determining the respective volume. The correlation of this volume with other 31 collected parameters was analyzed retrospectively. There was a significant correlation between the defect volume on the one hand, and the MRONJ stage, the number of performed operations, and the therapy invasiveness on the other hand. Furthermore, it could be shown that in one third of the cases no defects could be recognized in the 2D imaging by panoramic radiograph, while in the 3D data sets defects already had been demarcated. On the basis of these data, a computer-aided tool based on the principles of AI was developed and validated, which might allow the automated calculation of the 3D defect extension and classification of the MRONJ cases into a ranking system. In conclusion, preparation of a 3D image can be recommended for reliably making the diagnosis "MRONJ." Moreover, knowledge of the exact defect volume serves as a decision-making aid with regard to the choice of therapy, ensures intraoperative certitude, and allows an assessment of the prognosis.

Citing Articles

Advances in the Resection and Reconstruction of Midfacial Tumors Through Computer Assisted Surgery.

Wilkat M, Kubler N, Rana M Front Oncol. 2021; 11:719528.

PMID: 34737947 PMC: 8560787. DOI: 10.3389/fonc.2021.719528.

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