Sensitive Discrete Frequency Mid-Infrared Absorption Spectroscopy Using Digitally Referenced Detection.

Broadly tunable mid-infrared (IR) lasers, including quantum cascade lasers (QCL), are an asset for vibrational spectroscopy wherein high-intensity, coherent illumination can target specific spectral bands for rapid, direct chemical detection with microscopic localization. These emerging spectrometers are capable of high measurement throughputs with large detector signals from the high-intensity lasers and fast detection speeds as short as a single laser pulse, challenging the decades old benchmarks of Fourier transform infrared spectroscopy. However, noise in QCL emissions limits the feasible acquisition time for high signal-to-noise ratio (SNR) data. Here, we present an implementation that is broadly compatible with many laser-based spectrometer and microscope designs to address these limitations by leveraging high-speed digitizers and dual detectors to digitally reference each pulse individually. Digitally referenced detection (DRD) is shown to improve measurement sensitivity, with broad spectral indifference, regardless of imbalance due to dissimilarities among system designs or component manufacturers. We incorporated DRD into existing instruments and demonstrated its generalizability: a spectrometer with a 10-fold reduction in spectral noise, a microscope with reduced pixel dwell times to as low as 1 pulse while maintaining SNR normally achieved when operating 8-fold slower, and finally, a spectrometer to measure vibrational circular dichroism (VCD) with a ∼ 4-fold reduction in scan times. The approach not only proves versatile and effective but can also be tailored for specific applications with minimal hardware changes, positioning it as a simple and promising module for spectrometer designs using lasers.

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

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.

High-Resolution 3D Spin-Echo MRSI Using Interleaved Water Navigators, Sparse Sampling and Subspace-Based Processing.

This work presents a new method to achieve accelerated, high-resolution magnetic resonance spectroscopic imaging (MRSI) with spin-echo excitations. A new data acquisition strategy is proposed that integrates adiabatic refocusing, elimination of lipid suppression, rapid spatiospectral encoding with sparse (k,t)-space sampling, and interleaved water navigators. This integration leads to a significantly improved combination of volume coverage, spatial resolution (approximately 3 × 3.4 × 4 mm3) and speed (< 10 minutes), while eliminating additional scans for field mapping and coil sensitivity estimation. A data processing strategy that integrates parallel imaging reconstruction and subspace-based processing is devised to produce high-SNR spatiospectral reconstruction from the sparsely sampled, noisy and highresolution MRSI data. Promising in vivo results have been obtained to demonstrate the potential of the proposed method.Clinical relevance- The proposed method enabled volumetric MRSI with a nominal resolution of 3 × 3.4 × 4 mm3 in less than 10 minutes. With further developments and optimizations, the proposed method is expected to be useful for providing molecular-level information of brain functions and diseases, and has the potential to provide new biomarkers for disease diagnosis and treatment monitoring.