Abstract
Respiratory motion remains a source of major uncertainties in radiotherapy. Respiratory correlated computed tomography (referred to as 4DCT) serves as one way of reducing breathing artifacts in 3D-CTs and allows the investigation of tumor motion over time. The quality of the 4DCT images depends on the data acquisition scheme, which in turn is dependent on the vendor. Specifically, the only way Toshiba Aquilion LB CT scanners can reconstruct 4DCTs is a cycle-based reconstruction using triggers provided by an external surrogate signal. The accuracy is strongly dependent on the method of trigger generation. Two consecutive triggers are used to define a breathing cycle which is divided into respiratory phases of equal duration. The goal of this study is to identify if there are advantages in the usage of local-amplitude based sorting (LAS) of the respiration motion states, in order to reduce image artifacts and improve 4DCT quality. Furthermore, this study addresses the generation and optimization of a clinical workflow using as surrogate motion monitoring system the Sentinel (TM) (C-RAD AB, Sweden) optical surface scanner in combination with a Toshiba Aquilion LB CT scanner. For that purpose, a phantom study using 10 different breathing waveforms and a retrospective patient study using the 4DCT reconstructions of 10 different patients has been conducted. The error in tumor volume has been reduced from 2.9 +/- 3.7% to 2.7 +/- 2.6% using optimal cycle-based triggers (manipulated CBS) and to 2.7 +/- 2.2% using LAS in the phantom study. Moreover, it was possible to decrease the tumor volume variability from 5.0 +/- 3.6% using the original cycle-based triggers (original CBS) to 3.5 +/- 2.5% using the optimal triggers and to 3.7 +/- 2.7% using LAS in the patient data analysis. We therefore propose the usage of the manipulated CBS, also with regard to an accurate and safe clinical workflow.
Item Type: | Journal article |
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Faculties: | Medicine |
Subjects: | 600 Technology > 610 Medicine and health |
ISSN: | 0939-3889 |
Language: | English |
Item ID: | 63831 |
Date Deposited: | 19. Jul 2019, 12:14 |
Last Modified: | 04. Nov 2020, 13:42 |