Improving 3D-printing of megavoltage X-rays radiotherapy bolus with surface-scanner

Giovanna Dipasquale, Alexis Poirier, Yannick Sprunger, Johannes Wilhelmus Edmond Uiterwijk, Raymond Miralbell, Giovanna Dipasquale, Alexis Poirier, Yannick Sprunger, Johannes Wilhelmus Edmond Uiterwijk, Raymond Miralbell

Abstract

Background: Computed tomography (CT) data used for patient radiotherapy planning can nowadays be used to create 3D-printed boluses. Nevertheless, this methodology requires a second CT scan and planning process when immobilization masks are used in order to fit the bolus under it for treatment. This study investigates the use of a high-grade surface-scanner to produce, prior to the planning CT scan, a 3D-printed bolus in order to increase the workflow efficiency, improve treatment quality and avoid extra radiation dose to the patient.

Methods: The scanner capabilities were tested on a phantom and on volunteers. A phantom was used to produce boluses in the orbital region either from CT data (resolution ≈1 mm), or from surface-scanner images (resolution 0.05 mm). Several 3D-printing techniques and materials were tested. To quantify which boluses fit best, they were placed on the phantom and scanned by CT. Hounsfield Unit (HU) profiles were traced perpendicular to the phantom's surface. The minimum HU in the profiles was compared to the HU values for calibrated air-gaps. Boluses were then created from surface images of volunteers to verify the feasibility of surface-scanner use in-vivo.

Results: Phantom based tests showed a better fit of boluses modeled from surface-scanner than from CT data. Maximum bolus-to-skin air gaps were 1-2 mm using CT models and always < 0.6 mm using surface-scanner models. Tests on volunteers showed good and comfortable fit of boluses produced from surface-scanner images acquired in 0.6 to 7 min. Even in complex surface regions of the body such as ears and fingers, the high-resolution surface-scanner was able to acquire good models. A breast bolus model generated from images acquired in deep inspiration breath hold was also successful. None of the 3D-printed bolus using surface-scanner models required enlarging or shrinking of the initial model acquired in-vivo.

Conclusions: Regardless of the material or printing technique, 3D-printed boluses created from high-resolution surface-scanner images proved to be superior in fitting compared to boluses created from CT data. Tests on volunteers were promising, indicating the possibility to improve overall radiotherapy treatments, primarily for megavoltage X-rays, using bolus modeled from a high-resolution surface-scanner even in regions of complex surface anatomy.

Keywords: 3D printing; Additive materials; Bolus; DIBH; Radiotherapy; Surface-scanner.

Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

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Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Figures

Fig. 1
Fig. 1
a 3D model of the RANDO® phantom using CT-data with its corresponding bolus model (b) and 3D model of the phantom using surface-scanner data (c) with its corresponding bolus model (d)
Fig. 2
Fig. 2
The 3D-printed boluses created for this study. (a) The top three boluses are bolusCT based on CT-scan data. (b) The bottom three boluses are bolusS based on surface-scanner data. Abbreviations: ABS = Acrylonitrile butadiene styrene; PLA = Polylactic acid
Fig. 3
Fig. 3
a One slice of CT-scan of the RANDO® phantom with the ABS bolusS. b HU profile of the air gap between the RANDO® phantom and the ABS bolus. c CT-scan of an artificially created air gap of 1 mm. d HU profile of the 1 mm air gap
Fig. 4
Fig. 4
Left: Surface model of an ear split in 2 parts. Right: the 3D-printed boluses fitting the ear of a volunteer
Fig. 5
Fig. 5
Left, from top to bottom: Original acquired surface model of a breast; Bolus region cropped and divided in 2 subparts: upper part and lower part. Right: The 3D-printed boluses fitting the breast of the volunteer
Fig. 6
Fig. 6
a Creating the 3D model for the hand bolus using surface-scan data of a hand by extruding the region of interest. b Trimming the bolus model using flat planes on VXElements. c Testing the fit of the bolus on the subject’s hand. d Final 3D-printed bolus of the 4th and 5th knuckle

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