Human Bone Typing Using Quantitative Cone-Beam Computed Tomography.

Abstract

INTRODUCTION

Bone typing is crucial to enable the choice of a suitable implant, the surgical technique, and the evaluation of the clinical outcome. Currently, bone typing is assessed subjectively by the surgeon.

OBJECTIVE

The aim of this study is to establish an automatic quantification method to determine local bone types by the use of cone-beam computed tomography (CBCT) for an observer-independent approach.

METHODS

Six adult human cadaver skulls were used. The 4 generally used bone types in dental implantology and orthodontics were identified, and specific Hounsfield unit (HU) ranges (grey-scale values) were assigned to each bone type for identification by quantitative CBCT (qCBCT). The selected scanned planes were labelled by nonradiolucent markers for reidentification in the backup/cross-check evaluation methods. The selected planes were then physically removed as thick bone tissue sections for in vitro correlation measurements by qCBCT, quantitative micro-computed tomography (micro-CT), and quantitative histomorphometry.

RESULTS

Correlation analyses between the different bone tissue quantification methods to identify bone types based on numerical ranges of HU values revealed that the Pearson correlation coefficient of qCBCT with micro-CT and quantitative histomorphometry was R = 0.9 (P = .001) for all 4 bone types .

CONCLUSIONS

We found that qCBCT can reproducibly and objectively assess human bone types at implant sites.