Augmented reality for sentinel lymph node biopsy.

Autor: von Niederhäusern, Peter A., Seppi, Carlo, Sandkühler, Robin, Nicolas, Guillaume, Haerle, Stephan K., Cattin, Philippe C.
Zdroj: International Journal of Computer Assisted Radiology & Surgery; Jan2024, Vol. 19 Issue 1, p171-180, 10p
Abstrakt: Introduction: Sentinel lymph node biopsy for oral and oropharyngeal squamous cell carcinoma is a well-established staging method. One variation is to inject a radioactive tracer near the primary tumor of the patient. After a few minutes, audio feedback from an external hand-held γ -detection probe can monitor the uptake into the lymphatic system. Such probes place a high cognitive load on the surgeon during the biopsy, as they require the simultaneous use of both hands and the skills necessary to correlate the audio signal with the location of tracer accumulation in the lymph nodes. Therefore, an augmented reality (AR) approach to directly visualize and thus discriminate nearby lymph nodes would greatly reduce the surgeons' cognitive load. Materials and methods: We present a proof of concept of an AR approach for sentinel lymph node biopsy by ex vivo experiments. The 3D position of the radioactive γ -sources is reconstructed from a single γ -image, acquired by a stationary table-attached multi-pinhole γ -detector. The position of the sources is then visualized using Microsoft's HoloLens. We further investigate the performance of our SLNF algorithm for a single source, two sources, and two sources with a hot background. Results: In our ex vivo experiments, a single γ -source and its AR representation show good correlation with known locations, with a maximum error of 4.47 mm. The SLNF algorithm performs well when only one source is reconstructed, with a maximum error of 7.77 mm. For the more challenging case to reconstruct two sources, the errors vary between 2.23 mm and 75.92 mm. Conclusion: This proof of concept shows promising results in reconstructing and displaying one γ -source. Two simultaneously recorded sources are more challenging and require further algorithmic optimization. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
Externí odkaz: