Low-radiation dose scan protocol for preoperative imaging for dental implant surgery using deep learning-based reconstruction in multidetector CT

Yuki Sakai, Erina Kitamoto, Kazutoshi Okamura, Shinya Takarabe, Takashi Shirasaka, Ryoji Mikayama, Masatoshi Kondo, Masato Tatsumi, Tsukasa Kojima, Toyoyuki Kato, Kazunori Yoshiura

研究成果: ジャーナルへの寄稿学術誌査読

2 被引用数 (Scopus)

抄録

Objectives: This study aimed to investigate the impact of a deep learning-based reconstruction (DLR) technique on image quality and reduction of radiation exposure, and to propose a low-dose multidetector-row computed tomography (MDCT) scan protocol for preoperative imaging for dental implant surgery. Methods: The PB-1 phantom and a Catphan phantom 600 were scanned using volumetric scanning with a 320-row MDCT scanner. All scans were performed with a tube voltage of 120 kV, and the tube current varied from 120 to 60 to 40 to 30 mA. Images of the mandible were reconstructed using DLR. Additionally, images acquired with the 120-mA protocol were reconstructed using filtered back projection as a reference. Two observers independently graded the image quality of the mandible images using a 4-point scale (4, superior to reference; 1, unacceptable). The system performance function (SPF) was calculated to comprehensively evaluate image quality. The Wilcoxon signed-rank test was employed for statistical analysis, with statistical significance set at p value < 0.05. Results: There was no significant difference between the image quality acquired with the 40-mA tube current and reconstructed with the DLR technique (40DLR), and that acquired with the reference protocol (3.00, 3.00, p = 1.00). The SPF at 1.0 cycles/mm acquired with 40DLR was improved by 156.7% compared to that acquired with the reference protocol. Conclusions: Our proposed protocol, which achieves a two-thirds reduction in radiation dose, can provide a minimally invasive MDCT scan of acceptable image quality for dental implant surgery.

本文言語英語
ページ(範囲)517-526
ページ数10
ジャーナルOral Radiology
38
4
DOI
出版ステータス出版済み - 10月 2022

!!!All Science Journal Classification (ASJC) codes

  • 歯科学(その他)
  • 放射線学、核医学およびイメージング

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