Two new ad-hoc models of detection physics and their evaluation for navigated beta probe surface imaging

Intra-operative surface imaging with navigated beta probes in conjunction with positron-emitting radiotracers like ¹⁸F-FDG has been shown to enable control of tumor resection borders. We showed previously that employing iterative reconstruction (MLEM) in conjunction with an ad-hoc model of the detection physics (based on solid-angle geometry, SA) improves the image quality. In this study, we sampled the beta probe readings of a point source using a precision step-motor to generate a look-up-table (LUT) model. We also generated a simplified geometrical model (SG) based on this data set. To see how these two models influence the image quality compared to the old SA model, we reconstructed images from sparsely sampled datasets of a phantom with three hotspots using each model. The images yielded 76% (SA), 81% (SG), and 81% (LUT) mean NCC compared to the ground truth. The SG and LUT models, however, could resolve the hotspots better in the datasets where the detector-to-phantom distance was larger. Additionally, we compared the deviations of the SA and SG analytical models to the measured LUT model, where we found that the SG model gives estimates substantially closer to the actual beta probe readings than the previous SA model.