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Improvement of image quality of dentomaxillofacial region in ultra-high-resolution CT: a phantom study

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: The purpose of this study was to compare the image quality of ultra-high-resolution CT (U-HRCT) with that of conventional multidetector row CT (convCT) and demonstrate its usefulness in the dentomaxillofacial region. Methods: Phantoms were helically scanned with U-HRCT and convCT scanners using clinical protocols. In U-HRCT, phantoms were scanned in super-high-resolution (SHR) mode, and hybrid iterative reconstruction (HIR) and filtered-back projection (FBP) techniques were performed using a bone kernel (FC81). The FBP technique was performed using the same kernel as in convCT (reference). Two observers independently evaluated the 54 resulting images using a 5-point scale (5 = excellent diagnostic image quality; 4 = above average; 3 = average; 2 = subdiagnostic; and 1 = unacceptable). The system performance function (SPF) was calculated for a comprehensive evaluation of the image quality using the task transfer function and noise power spectrum. Statistical analysis using the Kruskal-Wallis test was performed to compare the image quality among the 3 protocols. Results: The observers assigned higher scores to images acquired with the SHRHIR and SHRFBP protocols than to those acquired with the reference (P < 0.0001 and P < 0.0001, respectively). The relative SPF value at 1.0 cycles/mm in SHRHIR and SHRFBP compared to the reference protocol were 151.5% and 45.6%, respectively. Conclusions: Through phantom experiments, this study demonstrated that U-HRCT can provide superior-quality images compared to conventional CT in the dentomaxillofacial region. The development of a better image reconstruction method is required to improve image quality and optimize the radiation dose.

Original languageEnglish
Pages (from-to)203-209
Number of pages7
JournalDentomaxillofacial Radiology
Volume54
Issue number3
DOIs
Publication statusPublished - Mar 1 2025

All Science Journal Classification (ASJC) codes

  • General Medicine

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