Impact of 4D image quality on the accuracy of target definition

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• 作者：Tine Bjørn Nielsen ; Christian Rønn Hansen…
• 关键词：4D ; CT ; Image artefact ; 4D ; CBCT ; Target motion ; Motion management ; NSCLC
• 刊名：Australasian Physical & Engineering Sciences in Medicine
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：39
• 期：1
• 页码：103-112
• 全文大小：1,484 KB
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• 作者单位：Tine Bjørn Nielsen (1) <br> Christian Rønn Hansen (1) <br> Jonas Westberg (1) <br> Olfred Hansen (2) (3) <br> Carsten Brink (1) (3) <br><br>1. Laboratory of Radiation Physics, Odense University Hospital, 5000, Odense, Denmark <br> 2. Department of Oncology, Odense University Hospital, Odense, Denmark <br> 3. Institute of Clinical Research, University of Southern Denmark, Odense, Denmark <br>
• 刊物主题：Biomedicine general; Biophysics and Biological Physics; Medical and Radiation Physics; Biomedical Engineering;
• 出版者：Springer Netherlands
• ISSN：1879-5447

文摘

Delineation accuracy of target shape and position depends on the image quality. This study investigates whether the image quality on standard 4D systems has an influence comparable to the overall delineation uncertainty. A moving lung target was imaged using a dynamic thorax phantom on three different 4D computed tomography (CT) systems and a 4D cone beam CT (CBCT) system using pre-defined clinical scanning protocols. Peak-to-peak motion and target volume were registered using rigid registration and automatic delineation, respectively. A spatial distribution of the imaging uncertainty was calculated as the distance deviation between the imaged target and the true target shape. The measured motions were smaller than actual motions. There were volume differences of the imaged target between respiration phases. Imaging uncertainties of >0.4 cm were measured in the motion direction which showed that there was a large distortion of the imaged target shape. Imaging uncertainties of standard 4D systems are of similar size as typical GTV–CTV expansions (0.5–1 cm) and contribute considerably to the target definition uncertainty. Optimising and validating 4D systems is recommended in order to obtain the most optimal imaged target shape.