Precise Hybrid-Actuation Robotic Fiber for Enhanced Cervical Disease Treatment

Treatment for high-grade precancerous cervical lesions and early-stage cancers, mainly affecting women of reproductive age, often involves fertility-sparing treatment methods. Commonly used local treatments for cervical precancers have shown the risk of leaving a positive cancer margin and engendering subsequent complications according to the precision and depth of excision. An intra-operative device that allows the careful excision of the disease while conserving healthy cervical tissue would potentially enhance such treatment. In this study, we developed a polymer-based robotic fiber measuring 150 mm in length and 1.7 mm in diameter, fabricated using a highly scalable fiber drawing technique. This robotic fiber utilizes a hybrid actuation mechanism, combining electrothermal and tendon-driven actuation mechanisms, thus enabling a maximum motion range of 46 mm from its origin with a sub-100 {\mu}m motion precision. We also developed control algorithms for the actuation methods of this robotic fiber, including predefined path control and telemanipulation, enabling coarse positioning of the fiber tip to the target area followed by a precise scan. The combination of a surgical laser fiber with the robotic fiber allows for high-precision surgical ablation. Additionally, we conducted experiments using a cervical phantom that demonstrated the robotic fiber's ability to access and perform high-precision scans, highlighting its potential for cervical disease treatments and improvement of oncological outcomes.

Variational autoencoders for tissue heterogeneity exploration from (almost) no preprocessed mass spectrometry imaging data

The paper presents the application of Variational Autoencoders (VAE) for data dimensionality reduction and explorative analysis of mass spectrometry imaging data (MSI). The results confirm that VAEs are capable of detecting the patterns associated with the different tissue sub-types with performance than standard approaches.