Purpose: To develop a novel scanning system of the pleural cavity surface using a handheld three-dimensional (3D) surface acquisition device. The integration of this technology will be utilized to develop light fluence modelling during pleural cavity Photodynamic Therapy (PDT).
Methods: A phantom model was developed from a modified ellipsoid shaped object (180mm x 180mm x 160mm) to maintain the relative dimensions of the pleural cavity space as observed during PDT. The external aspect of the structure was symmetrical and prefabricated of a hardened synthetic polymer. The interior surface was asymmetrically layered with non-reflective adhesive paper to create a non-uniformed surface topography. These surface characteristics were established in randomized X-Y-Z coordinates ranging in dimensions from 1-15mm. The phantom model was scanned with a handheld optical capturing device, acquiring digital measurements in actual value, and converted into a stereo lithography (STL) file. This specific device can reproduce large shapes of cavities (>30mm) while recognizing and differentiating surface characteristics within 1mm of accuracy.
Results: The handheld optical scanning device successfully captured the external shape of the pleural cavity phantom model and differentiated critical internal asymmetric surface characterizations in the X-Y-Z planes. Evaluation with CT model of the phantom confirm the accuracy to be less than 1mm.
Conclusion: These results present the first known successful validation of a handheld optical capturing device with high accuracy. We have demonstrated a novel ellipsoid phantom modelling system that can be acquired to data points of a greater ellipsoid modelling shape of 1mm-180mm. This modelling system can capture internal topographic characterizations ranging from 1-15mm that are representative of critical surface anatomies in the pleural cavity space. These findings suggest that this novel/capturing device is sensitive to this specific plural cavity phantom modelling application and can utilize a workflow capture to model more accurate light fluence during PDT.
Funding Support, Disclosures, and Conflict of Interest: NIH 1R01EB028778-01A, NIH 1P01CA 87971-01, NIH 1T90DE0854-01