Rapid azoospermia classification by stimulated Raman scattering and second harmonic generation microscopy.

Area of Science:

• Biomedical Optics
• Molecular Imaging
• Diagnostic Technology

Background:

• Traditional disease diagnosis methods struggle with spatial molecular information.
• Optical imaging offers biomarker exploration but limited species coverage.
• Comprehensive tissue microenvironment assessment is vital for diagnosis and therapy.

Purpose of the Study:

• To develop a multimodal imaging platform for simultaneous chemical and structural tissue analysis.
• To apply this platform for identifying molecular and structural signatures in azoospermia.
• To evaluate the diagnostic accuracy of the developed imaging and algorithm.

Main Methods:

• Development of a multimodal platform: stimulated Raman scattering and second harmonic generation microscopy (SRASH).
• Application of SRASH imaging to azoospermia patient samples.
• Utilizing a diagnostic algorithm, LiteBlendNet-Dx (LBNet-Dx), for classification.

Main Results:

• SRASH imaging successfully identified lipids, protein, and collagen contrasts in tissues.
• Unveiled distinct molecular and structural signatures for non-obstructive azoospermia.
• The LBNet-Dx algorithm achieved 100% sample-level accuracy in classifying azoospermia.
• SRASH imaging is a label-free technique, eliminating the need for sample pre-treatment.

Conclusions:

• SRASH imaging provides simultaneous chemical and structural information for comprehensive tissue analysis.
• This technique successfully identified biomarkers for non-obstructive azoospermia with high diagnostic accuracy.
• SRASH imaging holds significant potential for clinical translation in molecular imaging-based diagnosis and therapy.