Research Papers:

3D-Printed masks as a new approach for immobilization in radiotherapy – a study of positioning accuracy

Matthias Felix Haefner, Frederik Lars Giesel, Matthias Mattke, Daniel Rath, Moritz Wade, Jacob Kuypers, Alan Preuss, Hans-Ulrich Kauczor, Jens-Peter Schenk, Juergen Debus, Florian Sterzing and Roland Unterhinninghofen _

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Oncotarget. 2018; 9:6490-6498. https://doi.org/10.18632/oncotarget.24032

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Matthias Felix Haefner1,2,*, Frederik Lars Giesel3,*, Matthias Mattke1,2, Daniel Rath3, Moritz Wade3,4, Jacob Kuypers3,4, Alan Preuss3,4, Hans-Ulrich Kauczor5, Jens-Peter Schenk5, Juergen Debus1,2, Florian Sterzing2,6 and Roland Unterhinninghofen4,7

1Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany

2National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), 69120 Heidelberg, Germany

3Department of Nuclear Medicine, Heidelberg University Hospital, 69120 Heidelberg, Germany

4Institute of Antropomatics and Robotics, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany

5Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, 69120 Heidelberg, Germany

6Department of Radiation Oncology Kempten, 87439 Kempten, Germany

7Institute of Robotics and Mechatronics, German Aerospace Center, 82234 Oberpfaffenhofen-Weßling, Germany

*These authors contributed equally to the manuscript and share the first authorship

Correspondence to:

Matthias Felix Haefner, email: [email protected]

Keywords: immobilization; radiotherapy; 3D-printing; setup accuracy; head mask

Received: October 07, 2017     Accepted: January 02, 2018     Published: January 08, 2018


We developed a new approach to produce individual immobilization devices for the head based on MRI data and 3D printing technologies. The purpose of this study was to determine positioning accuracy with healthy volunteers.

3D MRI data of the head were acquired for 8 volunteers. In-house developed software processed the image data to generate a surface mesh model of the immobilization mask. After adding an interface for the couch, the fixation setup was materialized using a 3D printer with acrylonitrile butadiene styrene (ABS). Repeated MRI datasets (n=10) were acquired for all volunteers wearing their masks thus simulating a setup for multiple fractions. Using automatic image-to-image registration, displacements of the head were calculated relative to the first dataset (6 degrees of freedom).

The production process has been described in detail. The absolute lateral (x), vertical (y) and longitudinal (z) translations ranged between −0.7 and 0.5 mm, −1.8 and 1.4 mm, and −1.6 and 2.4 mm, respectively. The absolute rotations for pitch (x), yaw (y) and roll (z) ranged between −0.9 and 0.8°, −0.5 and 1.1°, and −0.6 and 0.8°, respectively. The mean 3D displacement was 0.9 mm with a standard deviation (SD) of the systematic and random error of 0.2 mm and 0.5 mm, respectively.

In conclusion, an almost entirely automated production process of 3D printed immobilization masks for the head derived from MRI data was established. A high level of setup accuracy was demonstrated in a volunteer cohort. Future research will have to focus on workflow optimization and clinical evaluation.

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