Visual grading experiments and optimization in CBCT dental implantology imaging: preliminary application of integrated visual grading regression

Ahmed Ali Al-Humairi, Ryan H.L. Ip, Kelly Spuur, Xiaoming Zheng, Boyen Huang

Research output: Contribution to journalArticlepeer-review

Abstract

This study uses a general formulation of integrated visual grading regression (IVGR) and applies it to cone beam computed tomography (CBCT) scan data related to anatomical landmarks for dental implantology. The aim was to assess and predict a minimum acceptable dose for diagnostic imaging and reporting. A skull phantom was imaged with a CBCT unit at various diagnostic exposures. Key anatomical landmarks within the images were independently reviewed by three trained observers. Each provided an overall image quality score. Statistical analysis was carried out to examine the acceptability of the images taken, using an IVGR analysis that was formulized as a three-stage protocol including defining an integrated score, develop-ment of an ordinal regression, and investigation of the possibility for dose reduction through estimated parameters. For a unit increase in the logarithm of radiation dose, the odds ratio that the integrated score for an image assessed by observers being rated in a higher category was 3.940 (95% confidence interval: 1.016–15.280). When assessed by the observers, the minimum dose required to achieve a 75% probability for an image to be classified as at least acceptable was 1346.91 mGy·cm2 dose area product (DAP), a 31% reduction compared to the 1962 mGy·cm2 DAP default dosage of the CBCT unit. The kappa values of the intra and inter-observer reliability indicated moderate agreements, while a discrepancy among observers was also identified because each, as expected, perceived visibility differently. The results of this work demonstrate the IVGR’s predictive value of dose saving in the effort to reduce dose to patients while maintaining reportable diagnostic image quality.
Original languageEnglish
Pages (from-to)133-145
Number of pages13
JournalRadiation and Environmental Biophysics
Volume61
Issue number1
Early online date05 Jan 2022
DOIs
Publication statusPublished - Mar 2022

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