Infrared spectroscopic laser scanning confocal microscopy for whole-slide chemical imaging

Abstract

Chemical imaging, especially mid-infrared spectroscopic microscopy, enables label-free biomedical analyses while achieving expansive molecular sensitivity. However, its slow speed and poor image quality impede widespread adoption. We present a microscope that provides high-throughput recording, low noise, and high spatial resolution where the bottom-up design of its optical train facilitates dual-axis galvo laser scanning of a diffraction-limited focal point over large areas using custom, compound, infinity-corrected refractive objectives. We demonstrate whole-slide, speckle-free imaging in ~3 min per discrete wavelength at 10× magnification (2 μm/pixel) and high-resolution capability with its 20× counterpart (1 μm/pixel), both offering spatial quality at theoretical limits while maintaining high signal-to-noise ratios (>100:1). The data quality enables applications of modern machine learning and capabilities not previously feasible - 3D reconstructions using serial sections, comprehensive assessments of whole model organisms, and histological assessments of disease in time comparable to clinical workflows. Distinct from conventional approaches that focus on morphological investigations or immunostaining techniques, this development makes label-free imaging of minimally processed tissue practical.

Fig. 1. Design overview and technical evaluations of label-free IR-LSM.

a Schematic is based on a galvanometer scanning confocal design with refractive optical assemblies custom-built for broadband performance and coupled to an EC-QCL array spanning the mid-IR spectral range. b Cross-sections of the interchangeable 10× and 20× objectives with design specifications are presented in the Supplementary Information (Supplementary Figs. S3 and 4) in conjunction with the tube and scan lens (Supplementary Figs. S5 and 6). Technical comparisons between FT-IR and IR-LSM configurations including: (c) system noise and SNR calculations (detail in Supplementary Table S3) with evaluations per (i) single pixel 100% lines in absorbance, (ii) spatial noise per wavenumber, (iii–iv) spectral and spatial noise obtained over time (IR-LSM: 100 bands, FT-IR: 4 cm⁻¹ spectral resolution) presented as mean values ± s.d. (n = 1000); d spatial resolution demonstrated with (i) subjective images of a Siemens star target, and with (iv–vi) objective MTF curves evaluated respectively at discrete wavenumbers using a slant-edge target; e applied field of view; and f single pixel measurements of absorbance and derivative spectra of SU-8 photoresist deposition. A comprehensive glossary of terms is in the Supplementary Information.

Fig. 2. Imaging sagittal sections of embryonic and adult zebrafish shown in false-color compositions of key IR absorption bands.

Embryonic zebrafish prepared at 28, 52, 76, 100, and 124 h post fertilization were imaged using (a) the presented IR-LSM instrument equipped with 20×/0.8 NA magnification, and (b) brightfield microscopy of H&E-stained sections of similarly prepared samples at the same stage. c Adult female zebrafish organ imaging was demonstrated with high-resolution insets of the (i) brain, (ii) gills, and (iii) ovary with the whole fish image presented in (d) and (e) fingerprint region spectra, at locations indicated by the pin symbol (from top to bottom), of tail muscle (navy), intestine (orange), liver (gold), cerebellum (purple), lamellar artery (green), primary growth stage I oocyte (teal) with germinal vesicle (burgundy), a small stage I oocyte (black), and degenerated oocyte (gray). f Contamination of PTFE microplastics in the zebrafish tissue sample with the Amide I absorbance band shown (grayscale) and detected PTFE signature at masked at 1213 cm⁻¹ and false-colored (green).

Fig. 3. Visualization of colon tissue under IR-LSM.

a False-color images reveal the distribution of phosphates and proteins in the tissue, where (i–iii) enlarged regions of submucosa, lumen and mucosa show comparable detail to (b) H&E-stained images of an adjacent tissue section observed under brightfield microscopy with corresponding regions as indicated. c Serial sections of the tissue block (100 slices, 5 µm thick) are imaged and computationally aligned to create a unique perspective rendering of the colon mucosa in 3D space. The corner insets show the cross-sectional position from which the corresponding view was generated from the original volumetric data, with the vantage angle as indicated by the black arrow.

Fig. 4. Demonstration of prostate cancer detection in a preparation of fresh frozen tissue sections.

a Rough annotations guided by pathologists are (b) transferred from H&E images to IR images on consecutive sections. c A deep learning model is trained to predict epithelial (epi.) malignancy using multispectral IR images. d Validation is performed on unstained samples containing benign glands, malignant glands, and benign glands surrounded by malignant tumors, each imaged with IR-LSM and represented in each row. e Target ROIs are shown on the Amide I map, representing a full microscopy slide, with (f) indicative IR-LSM 10× magnified field of view simulating real-time screening. g, h Comparative images of H&E-stained adjacent sections of the same tissue sample are shown with corresponding ROIs marked.