The use of 3D computer-aided design to optimize photoimmunotherapy catheter placement.
Publication/Presentation Date
7-1-2025
Abstract
BACKGROUND: There is limited information regarding how technical aspects of Photoimmunotherapy (PIT) catheter placement influences outcomes. We hypothesize that optimized 3D models of PIT treatment will demonstrate a higher volume of tumor treated compared to 3D models of actual intraoperative catheter placement.
METHODS: Clinical and radiographic data were obtained for RM-1929 photoimmunotherapy treated patients at a single institution from March 2016 to August 2021. 3D models were rendered to recreate photoimmunotherapy treatments based on intraoperative images. This was compared to an optimized therapy model for each instance of treatment. Comparisons were made between actual and optimized models based on total volume of tumor treated as well as number of cylindrical diffusers placed per treatment.
RESULTS: 3D models were generated for 9 PIT treatments in 6 patients. Optimized PIT models (N = 9) were matched and compared to actual PIT models (N = 9). Volume of tumor treated was higher for the optimized model compared to the actual treatment (22.6 vs 13.9 cm
CONCLUSION: In this post-hoc analysis, we demonstrate the importance of appropriate catheter placement in PIT as well as the feasibility of 3D computer aided design to simulate PIT catheter placement. Optimized 3D models demonstrated a higher volume of tumor treated compared to actual catheter placement. 3D computer aided design may be a useful adjunct to preoperative planning to optimize PIT catheter placement.
Volume
166
First Page
107365
Last Page
107365
ISSN
1879-0593
Published In/Presented At
Bridgham, K., Llerena, P., Kumar, A., Mastrolonardo, E., Banoub, R., Clark, T., Luginbuhl, A., Cognetti, D. M., & Curry, J. M. (2025). The use of 3D computer-aided design to optimize photoimmunotherapy catheter placement. Oral oncology, 166, 107365. https://doi.org/10.1016/j.oraloncology.2025.107365
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
40412308
Department(s)
Administration and Leadership
Document Type
Article