Periapical and panoramic radiographs as tools for early prediction of osteoporosis

Authors

Keywords:

panoramic radiograph, periapical radiograph, osteoporosis, bone density, morphometric index, artificial intelligence, machine learning.

Abstract

Introduction: Osteoporosis is a disease of the skeletal system caused by a gradual reduction in bone mineral density and deterioration of the microarchitecture, raising the risk of fracture. It is therefore necessary to implement diagnostic actions allowing early detection of mineral density alterations. Given the fact that dental radiographs are routine practice and make it possible to examine the bone structure of maxillae and mandibles, they have been proposed as primary tools for osteoporosis diagnosis.

Objective: Examine the viability of and progress in the use of periapical and panoramic radiographs as early predictors of osteoporosis.

Main remarks: A review was conducted about the combined use of panoramic and periapical radiographs. Both are machine learning techniques and morphometric indices.

General considerations: Panoramic and periapical radiographs may be useful for early prediction of osteoporosis. To achieve this end, dentists should have broad experience interpreting radiographic images or be specialists in oral radiology or maxillofacial surgery. On the other hand, computer tools based on machine learning are available which have obtained results in osteoporosis identification comparable to those obtained by radiologists. Those tools may support the work of less experienced professionals. Dentists should be the first to detect anomalous bone density changes, timely referring patients suspected of osteoporosis to the corresponding specialist.

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Published

2022-04-15

How to Cite

1.
Wilches Visbal JH, Castillo Pedraza MC, Saraví FD. Periapical and panoramic radiographs as tools for early prediction of osteoporosis. Rev Cubana Estomatol [Internet]. 2022 Apr. 15 [cited 2025 Feb. 23];59(2):e3936. Available from: https://revestomatologia.sld.cu/index.php/est/article/view/3936

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