Computed Tomography in Predicting the Mandibular Involvement by Oral Cancer, a Retrospective Study

Research output: Contribution to journalArticlepeer-review

Abstract

Despite several newer advancements in imaging technology, no new investigative modality has been introduced to clinical practice in the recent times that is accurate and yet cost-effective. As a result, the majority of cancer centers across the globe rely on computed tomography to diagnose and estimate bone involvement in oral cancer. Here, we evaluated the reliability of computed tomography in predicting the mandibular invasion in our cohort of oral cancer patients who had undergone mandibulectomy. In this retrospective study, conducted at a tertiary cancer care facility, the patients of oral cancer who were operated at our center between 1st October 2018 and 30th September 2020 were considered. The sensitivity, specificity, and positive and negative predictive values of the computed tomography in predicting bone involvement were calculated, and the survival analysis was performed to understand the implication of mandibular involvement on survival. The sensitivity and specificity of computed tomography in detecting bone involvement was around 77.9% and 76.7%, respectively, which were comparable with the other reports. In our series, only 30% of the resected mandible were involved by the disease. However, pathological involvement of the mandible did not affect the overall survival on univariate and multivariate analysis, but the presence of pathological positive cervical lymph nodes affected the survival. The outcome of our study suggests that the conservative mandibulectomy could be a sound oncological procedure particularly in those cases with no frank erosion of the mandible on computed tomography.

Original languageEnglish
Article number752018
Pages (from-to)1281-1288
Number of pages8
JournalIndian Journal of Otolaryngology and Head and Neck Surgery
Volume77
Issue number3
DOIs
Publication statusPublished - 03-2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Surgery
  • Otorhinolaryngology

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