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Determination of Optimum Exposure Parameters for Dentoalveolar Structures of the Jaws Using the CB MercuRay System with Cluster Signal-to-noise Analysis

Overview
Journal Oral Radiol
Specialty Radiology
Date 2018 Nov 29
PMID 30484205
Citations 1
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Abstract

Objective: To determine the optimum cone beam computed tomography exposure parameters for specific diagnostic tasks.

Methods: A Teflon phantom attached to a half-mandible in a large container was scanned in dental (D), implant (I), and panoramic (P) modes. An identical phantom in a small container was scanned in D mode. Both were scanned at 60, 80, 100, and 120 kV. We evaluated the image quality of five anatomical structures [dentinoenamel junction (1), lamina dura and periodontal ligament space (2), trabecular pattern (3), cortex-spongy bone junction (4), and pulp chamber and root canal (5)] and analyzed the diagnostic image quality with cluster signal-to-noise analysis. We then evaluated correlations between the two image qualities and calculated the threshold of acceptable diagnostic image quality. Optimum exposure parameters were determined from images with acceptable diagnostic image quality.

Results: For the small container, the optimum exposure parameters were D mode, 80 kV for (1), (3), and (4) and D mode, 100 kV for (5). For the large container, they were D mode, 120 kV for (1), (3), and (5) and D mode, 100 kV for (4). I mode, 120 kV reached the acceptable level for (4). No images reached the acceptable level for (2).

Conclusions: No optimum exposure parameters were identified for the evaluation of the lamina dura and periodontal ligament space. D mode was sufficient for the other structures; however, the tube voltage required for each structure differed. Smaller patients required lower tube voltage. I mode, 120 kV may be used for larger lesions.

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Relationship between image information content and observer performance in digital intraoral radiography.

Takarabe S, Okamura K, Kuramoto T, Tokumori K, Kato T, Yoshiura K Oral Radiol. 2022; 39(3):491-503.

PMID: 36289169 DOI: 10.1007/s11282-022-00662-7.

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