Inter-fractional Respiratory Motion Modelling from Abdominal Ultrasound: A Feasibility Study

Giger, Alina and Jud, Christoph and Nguyen, Damien and Krieger, Miriam and Zhang, Ye and Lomax, Antony J. and Bieri, Oliver and Salomir, Rares and Cattin, Philippe C.. (2019) Inter-fractional Respiratory Motion Modelling from Abdominal Ultrasound: A Feasibility Study. In: Predictive Intelligence in Medicine, 11843. Cham, pp. 11-22.

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Official URL: https://edoc.unibas.ch/80471/

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Motion management strategies are crucial for radiotherapy of mobile tumours in order to ensure proper target coverage, save organs at risk and prevent interplay effects. We present a feasibility study for an inter-fractional, patient-specific motion model targeted at active beam scanning proton therapy. The model is designed to predict dense lung motion information from 2D abdominal ultrasound images. In a pretreatment phase, simultaneous ultrasound and magnetic resonance imaging are used to build a regression model. During dose delivery, abdominal ultrasound imaging serves as a surrogate for lung motion prediction. We investigated the performance of the motion model on five volunteer datasets. In two cases, the ultrasound probe was replaced after the volunteer has stood up between two imaging sessions. The overall mean prediction error is 2.9 mm and 3.4 mm after repositioning and therefore within a clinically acceptable range. These results suggest that the ultrasound-based regression model is a promising approach for inter-fractional motion management in radiotherapy.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedical Engineering > Imaging and Computational Modelling > Center for medical Image Analysis & Navigation (Cattin)
UniBasel Contributors:Jud, Christoph and Nguyen, Damien and Bieri, Oliver and Cattin, Philippe Claude and Giger, Alina Tamara
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Series Name:Lecture Notes in Computer Science
Note:Publication type according to Uni Basel Research Database: Conference paper
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Last Modified:01 Feb 2021 12:50
Deposited On:01 Feb 2021 12:50

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