A Framework to Optimize Channel and Active Area Usage in Multicore Fibers for Needle Shape Sensing

This study develops a process for evaluating the impact of hardware design parameters on the performance of a stylet embedded with a multicore fiber (MCF) for shape sensing, to be used to guide the insertion of an interstitial brachytherapy needle. The MCF consists of seven cores (one central and six outer), with each core inscribed with fourteen fiber Bragg gratings (FBGs), called active areas (AAs). Hardware performance was evaluated using two datasets from distinct constant-curvature jigs. First, the influence of the number and spacing of AAs along the fiber on reconstruction accuracy was evaluated, which identified the AA configuration that yielded the lowest reconstruction errors. Channel configurations of seven-core and four-core fibers were analyzed similarly. Finally, recognizing that AA and channel performance are not entirely independent, a joint analysis was conducted to determine the globally optimal configuration of the stylet. Reconstruction with the optimized stylet achieved a reduction in tip error of 34% relative to the full-sensor configuration, a difference that is statistically significant $(\alpha =0.05,p=0.00005)$ for the designated calibration and validation dataset. This work provides practical guidance for MCF selection and establishes a new framework for post-fabrication optimization of multicore fibers.