Non-destructive Chemical Imaging of Bone Tissue for Intraoperative and Diagnostic Applications

Abstract

Bone is difficult to image using traditional histopathological methods, leading to challenges in intraoperative consultations needed in orthopedic oncology. However, intraoperative pathological evaluation is critical in guiding surgical treatment. In this study, we demonstrate that a multimodal imaging approach that combines stimulated Raman scattering (SRS) microscopy, two-photon fluorescence (TPF) microscopy, and second harmonic generation (SHG) microscopy can provide useful diagnostic information regarding intact bone tissue fragments from surgical excision or biopsy specimens. We imaged bone samples from 14 patient cases and performed comprehensive chemical and morphological analyses of both mineral and organic components of bone. Our main findings show that carbonate content combined with morphometric analysis of bone organic matrix can separate several major classes of bone cancer associated diagnostic categories with an average accuracy of >90%. This proof-of-principle study demonstrate that multimodal imaging and machine learning-based analysis of bony tissue can provide crucial diagnostic information for guiding clinical decisions in orthopedic oncology.