Artificial Intelligence-Assisted Stimulated Raman Histology: New Frontiers in Vibrational Tissue Imaging.

Area of Science:

• Biomedical Optics
• Histopathology
• Medical Imaging

Background:

• Frozen section biopsy is the current standard for rapid histologic evaluation but is labor-intensive and prone to variability.
• Existing methods face challenges in speed, cost, and diagnostic consistency, impacting clinical decisions.

Purpose of the Study:

• To review recent advances in Stimulated Raman Histology (SRH) as a rapid, label-free histopathology tool.
• To explore the integration of SRH with Artificial Intelligence (AI) for enhanced diagnostic capabilities.

Main Methods:

• Stimulated Raman Histology (SRH), a non-linear optical process, generates H&E-like images without labels.
• SRH utilizes stimulated Raman scattering (SRS) for high-intensity signal generation.
• AI algorithms are being integrated to augment SRH analysis.

Main Results:

• SRH provides high-resolution, conventional H&E-like images rapidly and without preprocessing.
• The technique overcomes limitations of conventional Raman scattering, offering high specificity.
• Integration with AI enhances precision and reduces reliance on manual interpretation.

Conclusions:

• SRH is a promising, non-invasive technology for intrasurgical histology, offering speed and accuracy.
• The synergy of SRH and AI presents a revolutionary approach to histopathology.
• This combination has the potential to significantly alleviate the burden on the global histopathology workforce.