Computer-aided diagnosis system for osteoporosis based on quantitative evaluation of mandibular lower border porosity using panoramic radiographs

Nakamoto, T., Hatsuta, S., Yagi, S., Verdonschot, R. G., Taguchi, A., & Kakimoto, N. (2020). Computer-aided diagnosis system for osteoporosis based on quantitative evaluation of mandibular lower border porosity using panoramic radiographs. Dentomaxillofacial Radiology, 49(4): 20190481. doi:10.1259/dmfr.20190481.
Objectives: A new computer-aided screening system for osteoporosis using panoramic radiographs was developed. The conventional system could detect porotic changes within the lower border of the mandible, but its severity could not be evaluated. Our aim was to enable the system to measure severity by implementing a linear bone resorption severity index (BRSI) based on the cortical bone shape.
Methods: The participants were 68 females (>50 years) who underwent panoramic radiography and lumbar spine bone density measurements. The new system was designed to extract the lower border of the mandible as region of interests and convert them into morphological skeleton line images. The total perimeter length of the skeleton lines was defined as the BRSI. 40 images were visually evaluated for the presence of cortical bone porosity. The correlation between visual evaluation and BRSI of the participants, and the optimal threshold value of BRSI for new system were investigated through a receiver operator characteristic analysis. The diagnostic performance of the new system was evaluated by comparing the results from new system and lumbar bone density tests using 28 participants.
Results: BRSI and lumbar bone density showed a strong negative correlation (p < 0.01). BRSI showed a strong correlation with visual evaluation. The new system showed high diagnostic efficacy with sensitivity of 90.9%, specificity of 64.7%, and accuracy of 75.0%.
Conclusions: The new screening system is able to quantitatively evaluate mandibular cortical porosity. This allows for preventive screening for osteoporosis thereby enhancing clinical prospects.
Publication type
Journal article
Publication date
2020

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