Early detection of acute mandibular osteomyelitis using computed tomography texture analysis. Systematic review.

Authors

  • Dr. Dharmapuri Govindhan Dharanidharan Private practice Mediscan Systems No. 197, Dr Natesan Road, Mylapore, Chennai 600004, Tamil Nadu, India.
  • Dr. Rashmi Raveendran MD Pathology, Assistant Professor, Vels Medical College and hospital Tamilnadu India.
  • Veerarakesh Undergraduate (MBBS), PSP Medical College Hospital and Research Institute, Tambaram Kanchipuram main road, Oragadam Panruti Kanchipuram district, Tamil Nadu 631604 India.
  • Dr. Karthik Shunmugavelu Assistant Professor, Department of Dentistry, PSP Medical College Hospital and Research Institute, Tambaram, Kanchipuram main road, Oragadam, Panruti, Kanchipuram district, Tamil Nadu 631604 India.

DOI:

https://doi.org/10.51168/sjhrafrica.v7i3.2504

Keywords:

Acute mandibular osteomyelitis, computed tomography, texture analysis, radiomics, early diagnosis, quantitative imaging, bone infection

Abstract

Background:

The delayed appearance of radiographic changes limits early diagnosis of acute mandibular osteomyelitis (AMO). Computed tomography (CT) texture analysis, a radiomics-based approach, enables quantitative evaluation of bone microarchitecture and may detect early disease. To systematically evaluate the diagnostic performance of CT texture analysis in the early detection of AMO.

Methods:

A systematic review was conducted in accordance with PRISMA 2020 guidelines. Electronic databases (PubMed, Scopus, Web of Science, Embase, ScienceDirect, Cochrane Library, and Google Scholar) were searched from January 2000 to October 2025. Studies assessing CT-based texture analysis for mandibular osteomyelitis or related jawbone pathologies were included. Data extraction covered imaging protocols, feature types, analytical methods, and diagnostic outcomes. Risk of bias was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Analytical Cross-Sectional Studies. This review was not registered in PROSPERO.

Results:

Five studies met the inclusion criteria. CT texture analysis demonstrated high diagnostic performance, with reported sensitivity, specificity, and AUC values ranging from 0.94 to 1.0 in the primary CT-based study. Consistently informative features included gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and gray-level size zone matrix (GLSZM) parameters. MRI-based radiomics studies supported similar discriminatory capability. The inclusion of perilesional regions improved model performance for osteomyelitis detection.

Limitations:

Evidence is limited by small sample sizes, retrospective designs, heterogeneity in imaging acquisition, segmentation methods, and a lack of standardized radiomic pipelines.

Conclusion:

CT texture analysis shows high potential for early detection of AMO by identifying microstructural bone alterations before conventional radiographic changes. Standardization and prospective validation are required for clinical translation.

Implications:

Integration of CT radiomics into diagnostic workflows may enable earlier intervention and improved outcomes in mandibular infections.

Author Biographies

  • Dr. Dharmapuri Govindhan Dharanidharan, Private practice Mediscan Systems No. 197, Dr Natesan Road, Mylapore, Chennai 600004, Tamil Nadu, India.

    is a dental practitioner based in Chennai, India, with clinical interests in oral diagnostic imaging and maxillofacial pathology. His work focuses on integrating imaging-based diagnostics into routine clinical practice.

  • Dr. Rashmi Raveendran, MD Pathology, Assistant Professor, Vels Medical College and hospital Tamilnadu India.

     is a pathologist based in Chennai with a special interest neuropathology and head & neck pathology.  Her work focuses on diagnostic histopathology and evidence based pathology practice with interdisciplinary collaboration in surgical pathology.

  • Veerarakesh, Undergraduate (MBBS), PSP Medical College Hospital and Research Institute, Tambaram Kanchipuram main road, Oragadam Panruti Kanchipuram district, Tamil Nadu 631604 India.

    is an undergraduate medical student with academic interests in radiology, diagnostic medicine, and clinical research methodologies.

  • Dr. Karthik Shunmugavelu, Assistant Professor, Department of Dentistry, PSP Medical College Hospital and Research Institute, Tambaram, Kanchipuram main road, Oragadam, Panruti, Kanchipuram district, Tamil Nadu 631604 India.

    is an Oral and Maxillofacial Pathologist and academician affiliated with PSP Medical College, Tamil Nadu, India. He holds multiple international memberships, including MFDS (RCS England and Glasgow), and has research interests in oral pathology, radiomics, and diagnostic innovations.

     

References

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Muraoka, H., Ito, K., Hirahara, N., Ichiki, S., Kondo, T., & Kaneda, T. (2022). Magnetic resonance imaging texture analysis in the quantitative evaluation of acute osteomyelitis of the mandibular bone. Dento maxillo facial radiology, 51(1), 20210321. https://doi.org/10.1259/dmfr.20210321

Ito K, Muraoka H, Hirahara N, Sawada E, Hirohata S, Otsuka K, Okada S, Kaneda T. Quantitative assessment of mandibular bone marrow using computed tomography texture analysis for detect stage 0 medication-related osteonecrosis of the jaw. European journal of radiology. 2021 Dec 1;145:110030. https://doi.org/10.1016/j.ejrad.2021.110030

Santos, G. N. M., da Silva, H. E. C., Ossege, F. E. L., Figueiredo, P. T. S., Melo, N. S., Stefani, C. M., & Leite, A. F. (2023). Radiomics in bone pathology of the jaws. Dento maxillo facial radiology, 52(1), 20220225. https://doi.org/10.1259/dmfr.20220225

Jia Q, Zheng H, Lin J, Guo J, Fan S, Alimujiang A, Wang X, Fu L, Xie Z, Ma C, Wang J. Optimizing diagnosis and surgical decisions for chronic osteomyelitis through radiomics in the precision medicine era. Frontiers in Bioengineering and Biotechnology. 2024 May 10;12:1315398.https://doi.org/10.3389/fbioe.2024.1315398

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Published

2026-03-30

Issue

Vol. 7 No. 3 (2026): March 2026 Issue

Section

Section of Pathology, and Histopathology

License

Copyright (c) 2026 Dr. Dharmapuri Govindhan Dharanidharan, Dr. Rashmi Raveendran, Veerarakesh, Dr. Karthik Shunmugavelu

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Early detection of acute mandibular osteomyelitis using computed tomography texture analysis. Systematic review. (2026). Student’s Journal of Health Research Africa, 7(3), 9. https://doi.org/10.51168/sjhrafrica.v7i3.2504

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