Extended Multiplicative Signal Correction for Infrared Microspectroscopy of Heterogeneous Samples with Cylindrical Domains

Abstract

Optical scattering corrections are invoked to computationally distinguish between scattering and absorption contributions to recorded data in infrared (IR) microscopy, with a goal to obtain an absorption spectrum that is relatively free of the effects of sample morphology. Here, we present a modification of the extended multiplicative signal correction (EMSC) approach that allows for spectral recovery from fibers and cylindrical domains in heterogeneous samples. The developed theoretical approach is based on exact Mie theory for infinite cylinders. Although rigorous Mie theory implies utilization of comprehensive and time-consuming calculations, we propose to change the workflow of the original EMSC algorithm to minimize extensive calculations for each recorded spectrum at each iteration step. This makes the modified EMSC approach practical for routine use. First, we tested our approach using synthetic data derived from a rigorous model of scattering from cylinders in an IR microscope. Second, we applied the approach to Fourier transform IR (FT-IR) microspectroscopy data recorded from filamentous fungal and cellulose samples with pronounced fiber-like shapes. While the corrected spectra show greatly reduced baseline offsets and consistency, strongly absorbing regions of the spectrum require further refinement. The modified EMSC algorithm broadly mitigates the effects of scattering, offering a practical approach to more consistent and accurate spectra from cylindrical objects or heterogeneous samples with cylindrical domains.

Attenuated Total Reflection (ATR) Micro-Fourier Transform Infrared (Micro-FT-IR) Spectroscopy to Enhance Repeatability and Reproducibility of Spectra Derived from Single Specimen Organic-Walled Dinoflagellate Cysts

“…Extensions to basic EMSC exist to account for specific types of light scattering such as resonant Mie-type scattering (RMieS-EMSC) that dominantly occur in spherical scatterers 54,55,59 or scattering in fibers and cylindrical domains. 97 It is however still unclear if EMSC-based algorithms are able to correct perfectly and extract pure absorbance spectra, a feat which might only be currently achievable by other modeling and deep learning approaches, 58,60–62,64 which are nonlinear by nature. 98 For some deep learning classification algorithms, the best classification results are observed without any prior data processing, except for assignment of a target class and splitting of the data set into training, validation, and testing sets.…”

The Bouguer‐Beer‐Lambert Law: Shining Light on the Obscure

“…[66,67] Shape effects may then also play a role. [68] Unfortunately, there is no analytical way to correct such features. It seems, however, that their influence on the spectra is diminished the higher the densities of the scattering centres are.…”

Analysis of Fixed and Live Single Cells Using Optical Photothermal Infrared with Concomitant Raman Spectroscopy

“…These preservation methods allow the biochemistry to be captured at a specific moment in time and have enabled the elucidation of significant information on cell behavior, including insights into disease progression and response to treatment across a wide range of cell types. − The fixation of cellular samples and their presentation in dried form, however, introduces a range of spectral artifacts, most notably dispersive artifacts such as Mie and resonant Mie scattering. , These are most prominent at sample RI discontinuities, such as sample-air gaps and edges, which lead to potential severe spectral distortions. While there are algorithms available to attempt to correct for some of these, − often such corrections are not entirely accurate in reproducing a nondistorted spectrum. Reference spectra are required, and algorithms are computationally intensive; hence, it is preferable to eliminate these experimentally using some form of RI matching.…”