Tissue sections offer the opportunity to understand a patient's condition, to make better prognostic evaluations and to select optimum treatments, as evidenced by the place pathology holds today in clinical practice. Yet, there is a wealth of information locked up in a tissue section that is only partially accessed, due mainly to the limitations of tools and methods. Often tissues are assessed primarily based on visual analysis of one or two proteins, or 2-3 DNA or RNA molecules. Even while analysis is still based on visual perception, image analysis is starting to address the variability of human perception. This is in contrast to measuring characteristics that are substantially out of reach of human perception, such as parameters revealed through co-expression, spatial relationships, heterogeneity, and low abundance molecules. What is not routinely accessed is the information revealed through simultaneous detection of multiple markers, the spatial relationships among cells and tissue in disease, and the heterogeneity now understood to be critical to developing effective therapeutic strategies. Our purpose here is to review and assess methods for multiplexed, quantitative, image analysis based approaches, using new multicolor immunohistochemistry methods, automated multispectral slide imaging, and advanced trainable pattern recognition software. A key aspect of our approach is presenting imagery in a workflow that engages the pathologist to utilize the strengths of human perception and judgment, while significantly expanding the range of metrics collectable from tissue sections and also provide a level of consistency and precision needed to support the complexities of personalized medicine.

IMPORTANCE PD-L1 (programmed cell death ligand 1) immunohistochemistry (IHC), tumor mutational burden (TMB), gene expression profiling (GEP), and multiplex immunohistochemistry/immunofluorescence (mIHC/IF) assays have been used to assess pretreatment tumor tissue to predict response to anti-PD-1/PD-L1 therapies. However, the relative diagnostic performance of these modalities has yet to be established.OBJECTIVE To compare studies that assessed the diagnostic accuracy of PD-L1 IHC, TMB, GEP, and mIHC/IF in predicting response to anti-PD-1/PD-L1 therapy.

The ability to image and quantitate fluorescently labeled markers in vivo has generally been limited by autofluorescence of the tissue. Skin, in particular, has a strong autofluorescence signal, particularly when excited in the blue or green wavelengths. Fluorescence labels with emission wavelengths in the near-infrared are more amenable to deep-tissue imaging, because both scattering and autofluorescence are reduced as wavelengths are increased, but even in these spectral regions, autofluorescence can still limit sensitivity. Multispectral imaging (MSI), however, can remove the signal degradation caused by autofluorescence while adding enhanced multiplexing capabilities. While the availability of spectral "libraries" makes multispectral analysis routine for well-characterized samples, new software tools have been developed that greatly simplify the application of MSI to novel specimens.

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Acousto-optic tunable filters (AOTF) and liquid crystal tunable filters (LCTF) are evaluated for their suitability as fluorescence microscopy imaging spectrometers. AOTFs are solid-state birefringent crystals that provide an electronically tunable spectral notch passband in response to an applied acoustic field. LCTFs also provide a notch passband that can be controlled by incorporating liquid crystal waveplate retarders within a Lyot birefringent filter. In this paper, spectroscopic performance and imaging quality are contrasted by evaluation of model systems. Studies include transmission imaging of standard resolution targets, multispectral fluorescence emission imaging of tagged polystyrene microspheres, and immunofluorescence imaging of neurotransmitters within rat-brainstem thin sections. In addition, the first use of LCTFs for Raman microscopy is demonstrated. Raman microscopy is a noninvasive spectral imaging technique that can provide chemically significant image contrast complementary to fluorescence microscopy without the use of stains or tags.