Abstract
Background
Photoimmunotherapy is a treatment modality that induces targeted cell death by binding a molecular-targeted drug activated by infrared light to the tumor cells and subsequently illuminating the lesion with infrared light. For deep lesions, a needle catheter is used to puncture the tumor, and an illumination fiber (cylindrical diffuser) is inserted into the catheter lumen for internal illumination. However, it can be challenging to place the cylindrical diffusers in an appropriate position as the deep lesions cannot be often confirmed accurately during surgery.
Materials and methods
We have developed "SlicerPIT", a planning simulation software for photoimmunotherapy. SlicerPIT allows users to place the cylindrical diffuser with its illumination range on preoperative images in 2D and 3D and export the planning data to external image-guided surgical navigation systems. We performed seven cycles of photoimmunotherapy with SlicerPIT in three patients with recurrent head and neck cancer.
Results
Preoperative planning for photoimmunotherapy was conducted using SlicerPIT, which could be imported into the navigation system. During the operation, we punctured the needle catheters along with the treatment plan on the navigation screen. Subsequently, intraoperative CT imaging was performed and overlaid with the preoperative treatment plan to confirm the alignment of the cylindrical diffusers as planned, followed by infrared light illumination. Postoperative imaging showed necrosis and shrinkage of the entire tumor in all cycles.
Conclusion
SlicerPIT allows for detailed preoperative treatment planning and accurate puncture. It may be a valuable tool to improve the accuracy of photoimmunotherapy for deep lesions and improve patient outcomes.
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Acknowledgements
This work was supported by JSPS KAKENHI Grant Numbers JP23K15881, JP21K10037, JP21K07717.
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Suzuki, T., Kano, S., Suzuki, M. et al. SlicerPIT: software development and implementation for planning and image-guided therapy in photoimmunotherapy. Int J Clin Oncol (2024). https://doi.org/10.1007/s10147-024-02516-0
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DOI: https://doi.org/10.1007/s10147-024-02516-0