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Location: Marriott Marquis
Location: Marriott Marquis
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PQA 02 - PQA 02 Physics Poster Q&A

2418 - Mobile LIDAR and 3D Sensors as a Feasible Method for the Preparation of 3D Printed Custom Boluses

Sunday, September 29, 2024
4:45 PM - 6:00 PM ET
Location: Hall C

Screen: 18

A. Bochynska, A. Borkowska, P. Mroczkowski, A. Walewska, E. Fujak, and M. J. Spalek; Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland

Purpose/Objective(s): To evaluate the technology of creating 3D printed boluses without a prior computed tomography scan using widely available, inexpensive mobile LIDAR and 3D sensors.

Introduction: Gel, thermoplastic, or wax boluses, have several shortcomings, including problems with proper bolus fitting to the surface. Some of these problems can be solved by using personalized 3D printed boluses. Currently, most 3D boluses are generated based on the computed tomography (CT) scans used for treatment planning. Such a method has a disadvantage of assuming perfect placement of the "virtual" bolus". The objective of the study is to develop and validate an adaptable technology for 3D printing of boluses for high-conformal radiotherapy using mobile devices equipped with LIDAR and 3D sensors, which will allow to improve dose distribution in anatomically challenging sites without prior CT. Materials/

Methods: We investigated two methods of 3D-printed bolus creation, namely LIDAR available on smartphones and a commercially available mobile smartphone-attachable optical sensor. We used two types of filaments, thermoplastic polyurethane (TPU) and polylactic acid (PLA), as well as a standard 0.5 cm gel bolus. Based on a previous dosimetric study, we found that 0.5 cm TPU with 100% infill and 1 cm PLA with 50% infill present similar dosimetric parameters to 0.5 cm gel bolus. Therefore, we used those thicknesses in 3D-printing. We prepared boluses for three anatomically-challenging sites, namely the face, corner of the eye, and thoracic wall. After scanning, bolus printing, and placement, we performed relevant CT scans. We aimed to calculate the volume of the air gap between the target volume and skin surface made for tumor models with 3D boluses and standard gel boluses performed on an anthropomorphic phantom. For all cases, the airspace volumes were measured using the lung window of Hounsfield units scale with the same threshold parameters.

Results: Results are presented in Tab. 1. The lowest volumes of air gaps were achieved by using 3D boluses created by scanning the surface with an optical sensor, whereas the highest volumes were generated by the placement of conventional gel boluses. Table 1. Air gaps volumes using different scanning techniques and materials

Conclusion: The investigated method enabled the preparation of fast, cheap, and accurate 3D-printed boluses that are superior to conventional gel boluses used in clinical practice.
Scanning technique Anatomical site Material Air gap volume [cm3]
Optical sensor Chest wall Polylactic acid 0.39
Optical sensor Chest wall Polylactic acid 0.58
None Chest wall Gel 3.12
Optical sensor Corner of the eye Polylactic acid 0.05
LIDAR Corner of the eye Polylactic acid 1.41
Optical sensor Corner of the eye Thermoplastic polyurethane 0.09
LIDAR Corner of the eye Thermoplastic polyurethane 1.1
Optical sensor Face Polylactic acid 0.01
Optical sensor Face Polylactic acid 0.03
Optical sensor Face Polylactic acid 0.01
Optical sensor Face Polylactic acid 0.04