Histopathological correlations of bulk tissue polarimetric images: Case study

Deep learning-assisted identification and localization of ductal carcinoma from bulk tissue in-silico models generated through polarized Monte Carlo simulations

Despite significant progress in diagnosis and treatment, breast cancer remains a formidable health challenge, emphasizing the continuous need for research. This simulation study uses polarized Monte Carlo approach to identify and locate breast cancer. The tissue model Mueller matrix derived from polarized Monte Carlo simulations provides enhanced contrast for better comprehension of tissue structures. This study explicitly targets tumour regions found at the tissue surface, a possible scenario in thick tissue sections obtained after surgical removal of breast tissue lumps. We use a convolutional neural network for the identification and localization of tumours. Nine distinct spatial positions, defined relative to the point of illumination, allow the identification of the tumour even if it is outside the directly illuminated area. A system incorporating deep learning techniques automates processes and enables real-time diagnosis. This research paper aims to showcase the concurrent detection of the tumour's existence and position by utilizing a Convolutional Neural Network (CNN) implemented on depolarized index images derived from polarized Monte Carlo simulations. The classification accuracy achieved by the CNN model stands at 96%, showcasing its optimal performance. The model is also tested with images obtained from in-vitro tissue models, which yielded 100% classification accuracy on a selected subset of spatial positions.

Reflection mode polarimetry guides laser mass spectrometry to diagnostically important regions of human breast cancer tissue

To enhance the clinical utility of mass spectrometry (MS), lengthy dwell times on less informative regions of patient specimens (e.g., adipose tissue in breast) must be minimized. Additionally, a promising variant of MS known as picosecond infrared laser MS (PIRL-MS) faces further challenges, namely, lipid contamination when probing adipose tissue. Here we demonstrate on several thick non-sectioned resected human breast specimens (healthy and malignant) that reflection-mode polarimetric imaging can robustly guide PIRL-MS toward regions devoid of significant fat content to (1) avoid signal contamination and (2) shorten overall MS analysis times. Through polarimetric targeting of non-fat regions, PIRL-MS sampling revealed feature-rich spectral signatures including several known breast cancer markers. Polarimetric guidance mapping was enabled by circular degree-of-polarization (DOP) imaging via both Stokes and Mueller matrix polarimetry. These results suggest a potential synergistic hybrid approach employing polarimetry as a wide-field-imaging guidance tool to optimize efficient probing of tissue molecular content using MS.

Characterizing colon cancer stages through optical polarimetry-assisted digital staining

Tissue polarimetry has been gaining importance in extracting useful diagnostic information from the structural attributes of tissues, which vary in response to the tissue health status and hence find great potential in cancer diagnosis. However, the complexities associated with cancer make it challenging to isolate the characteristic changes as the tumor progresses using polarimetry. This study attempts to experimentally characterize the polarimetric behavior in colon cancer associated with various stages of development. Bulk and unstained sections of normal and tumor colon tissue were imaged in the reflection and transmission polarimetry configurations at low and high imaging resolutions using an in-house developed Mueller polarimeter. Through this study, we observed that the information about the major contributors of scattering in colon tissue, manifesting in depolarization and retardance, can be obtained from the bulk tissue and unstained sections. These parameters aid in characterizing the polarimetric changes as the colon tumor progresses. While the unstained colon section best indicated the depolarization contrast between normal and tumor, the contrast through the retardance parameter was more pronounced in the bulk colon tissue. The results suggest that the polarimetric "digitally stained" images obtained by Mueller polarimetry are comparable with the bulk tissue counterparts, making it useful for characterizing colon cancer tissues across different stages of development.

Toward the development of a polarimetric tool to diagnose the fibrotic human ventricular myocardium

SIGNIFICANCE

Optical polarimetry is an emerging modality that effectively quantifies the bulk optical properties that correlate with the anisotropic structural properties of cardiac tissues. We demonstrate the application of a polarimetric tool for characterizing healthy and fibrotic human myocardial tissues efficiently with a high degree of accuracy.

AIM

The study was aimed to characterize the myocardial tissues from the left ventricle and right ventricle of N  =  7 control and N  =  10 diseased subjects. The diseased subjects were composed of two groups: N  =  7 with rheumatic heart disease (RHD) and N  =  3 with myxomatous valve (MV) disease.

APPROACH

A portable, affordable, and accurate linear polarization-based diagnostic tool is developed to measure the degree of linear polarization (DOLP) of the myocardial tissues while working at a wavelength of 850 nm.

RESULTS

The sensitivity, specificity, and accuracy of the polarimetric tool in distinguishing the control group from the RHD group were found to be 73.33%, 76.92%, and 75%, respectively, and from the MV group were 91.6%, 62.5%, and 80%, respectively, which demonstrates the efficacy of the polarimetric tool to distinguish the healthy myocardial tissues from diseased tissues.

CONCLUSIONS

We have successfully developed a polarimetric tool that can aid cardiologists in characterizing the myocardial tissues in conjunction with endomyocardial biopsy. This work should be followed up with experiments on a large cohort of control and diseased subjects. We intend to create and develop a probe to quantify the DOLP of in vivo heart tissue during surgery.

Study of the spatial scale stability of Mueller matrix parameters for textural characterization of biological tissues

Mueller matrix imaging polarimetry (MMIP) is a promising technique for the textural characterization of biological tissue structures. To reveal the influence of imaging magnification on the robustness of Mueller matrix parameters (MMPs), the spatial scale stability of MMPs was studied. We established a new MMIP detector and derived the mathematical model of the spatial scale stability of MMPs. The biological tissues with well-defined structural components were imaged under different magnifications. Then, we compared and analyzed the textural features of the MMPs in the resulting images. The experimental results match the predictions of the mathematical model in these aspects: (a) magnification exhibits a strong nonlinear effect on the textural contrasts of MMPs images; (b) higher magnification does not necessarily lead to superior contrast for textural characterization; and (c) for different biological tissues, MMPs contrasts can be optimized differently, with some showing superior results. This study provides a reference for the experimental design and operation of the MMIP technique and is helpful for improving the characterization ability of MMPs.

Toward the development of portable light emitting diode-based polarization spectroscopy tools for breast cancer diagnosis

A robust, affordable and portable light emitting diode-based diagnostic tools (POLS-NIRDx) using a polarization-sensitive (linear as well as circular polarization) technique were designed and developed to quantify the degree of linear polarization (DOLP), degree of circular polarization (DOCP). The study was performed on malignant (invasive ductal carcinoma) and adjacent normal ex-vivo biopsy tissues excised from N = 10 patients at the operating wavelengths of 850 and 940 nm. The average DOLP and DOCP values were lower for malignant than adjacent normal while operating at 850 and 940 nm. The highest accuracy was observed for DOLP (100%) and DOCP (80%) while operating at 850 nm, which reduced (80% for DOLP and 65% for DOCP) at 940 nm. This pilot study can be utilized as a differentiating factor to delineate malignant tissues from adjacent normal tissues.