Introduction: Zygomatic fractures can be diagnosed with either computed tomography (CT) or direct digital radiography (DR). The aim of the present study was to assess the effect of CT dose reduction on the preference for facial CT versus DR for accurate diagnosis of isolated zygomatic fractures. Materials and methods: Eight zygomatic fractures were inflicted on four human cadavers with a free fall impactor technique. The cadavers were scanned using eight CT protocols, which were identical except for a systematic decrease in radiation dose per protocol, and one DR protocol. Single axial CT images were displayed alongside a DR image of the same fracture creating a total of 64 dual images for comparison. A total of 54 observers, including radiologists, radiographers and oral and maxillofacial surgeons, made a forced choice for either CT or DR. Results: Forty out of 54 observers (74%) preferred CT over DR (all with P < 0.05). Preference for CT was maintained even when radiation dose reduced from 147.4 mSv to 46.4 mSv (DR dose was 6.9 mSv). Only a single out of all raters preferred DR (P ¼ 0.0003). The remaining 13 observers had no significant preference. Conclusion: This study demonstrates that preference for axial CT over DR is not affected by substantial (~70%) CT dose reduction for the assessment of zygomatico-orbital fractures.
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Chest imaging plays a pivotal role in screening and monitoring patients, and various predictive artificial intelligence (AI) models have been developed in support of this. However, little is known about the effect of decreasing the radiation dose and, thus, image quality on AI performance. This study aims to design a low-dose simulation and evaluate the effect of this simulation on the performance of CNNs in plain chest radiography. Seven pathology labels and corresponding images from Medical Information Mart for Intensive Care datasets were used to train AI models at two spatial resolutions. These 14 models were tested using the original images, 50% and 75% low-dose simulations. We compared the area under the receiver operator characteristic (AUROC) of the original images and both simulations using DeLong testing. The average absolute change in AUROC related to simulated dose reduction for both resolutions was <0.005, and none exceeded a change of 0.014. Of the 28 test sets, 6 were significantly different. An assessment of predictions, performed through the splitting of the data by gender and patient positioning, showed a similar trend. The effect of simulated dose reductions on CNN performance, although significant in 6 of 28 cases, has minimal clinical impact. The effect of patient positioning exceeds that of dose reduction.
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Abstract Background: We studied the relationship between trismus (maximum interincisor opening [MIO] ≤35 mm) and the dose to the ipsilateral masseter muscle (iMM) and ipsilateral medial pterygoid muscle (iMPM). Methods: Pretreatment and post-treatment measurement of MIO at 13 weeks revealed 17% of trismus cases in 83 patients treated with chemoradiation and intensity-modulated radiation therapy. Logistic regression models were fitted with dose parameters of the iMM and iMPM and baseline MIO (bMIO). A risk classification tree was generated to obtain optimal cut-off values and risk groups. Results: Dose levels of iMM and iMPM were highly correlated due to proximity. Both iMPM and iMM dose parameters were predictive for trismus, especially mean dose and intermediate dose volume parameters. Adding bMIO, significantly improved Normal Tissue Complication Probability (NTCP) models. Optimal cutoffs were 58 Gy (mean dose iMPM), 22 Gy (mean dose iMM) and 46 mm (bMIO). Conclusions: Both iMPM and iMM doses, as well as bMIO, are clinically relevant parameters for trismus prediction.
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