Advancing Biomedical Diagnostics with Photothermal Mid-Infrared Spectroscopic Imaging

Vibrational spectroscopy has emerged as a powerful tool for biochemical profiling of tissue sections, especially in complex biomedical contexts such as cancer, where conventional spectroscopy often lacks sufficient sensitivity and specificity. Mid-Infrared Spectroscopic Imaging (MIRSI) represents a major step forward, uniting the molecular precision of vibrational spectroscopy with the spatial detail of microscopy. When paired with machine learning, MIRSI enables label-free, quantitative classification of tissue subtypes and disease grades, transforming diagnostic capabilities. Building on this foundation, photothermal MIRSI provides further gains in resolution, sensitivity, and flexibility, addressing limitations of earlier approaches. Here, we present a comparative evaluation of photothermal MIRSI techniques across diverse biomedical applications, highlighting their diagnostic potential.

Lupus Nephritis (LN) is an autoimmune kidney disease whose diagnosis is hindered by its subtle early pathology and similarity to other renal conditions. We demonstrate how photothermal MIRSI detects minute molecular changes, offering more accurate LN diagnosis. For ovarian cancer, photothermal MIRSI provides high-resolution tissue segmentation and precise identification of malignant regions, enabling improved stratification and treatment planning. Beyond oncology, photothermal MIRSI also distinguishes bone disorders such as osteosclerosis via unique spectroscopic signatures. Extending further, polarization MIRSI enables mapping of fine collagen fiber orientations, a critical parameter for grading bone marrow fibrosis. Together, these studies illustrate the transformative potential of photothermal MIRSI to expand the frontiers of biomedical imaging and diagnostics. By capturing subtle molecular and structural signatures that escape traditional methods, photothermal MIRSI paves the way for earlier detection, more accurate grading, and ultimately improved clinical outcomes.