Automatic detection of head and neck squamous cell carcinoma on histologic slides using hyperspectral microscopic imaging

Ma, Ling; Little, James V.; Chen, Amy Y.; Myers, Larry L.; Sumer, Baran D.; Fei, Baowei

doi:10.1117/1.jbo.27.4.046501

Cited by 15 publications

(16 citation statements)

References 47 publications

(61 reference statements)

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“…Normally, the pathological diagnosis of HNSCC can be implemented with hematoxylin and eosin (H&E)-stained slides with a regular microscope. Certain features that are related to HNSCC, including keratinization, atypical mitoses, and enlarged nuclei size, can be clearly observed in RGB histology images of the H&E-stained slides 4 , 5 . However, the tumor microenvironment consists of multiple biochemical, mechanical, and structural signals, and some of the major structural components, such as collagen, 6 , 7 are not obviously noticeable in those images.…”

Section: Introductionmentioning

confidence: 99%

“…Our group has investigated several machine learning and deep learning algorithms for head and neck cancer detection in histological slides based on HSI and proved the usefulness of HSI. We carried out HNSCC detection based on the morphology and spectral signatures of the nuclei, respectively, and we found that both spatial and spectral information have significant impacts on the classification results 4 . Using an inception-based deep neural network, we implemented whole-slide HNSCC detection and proved that HSI outperforms RGB 16 , 17 Furthermore, by employing a pre-trained video transformer on hyperspectral microscopic data, an detection accuracy of 89.64% was achieved in whole-slide thyroid cancer histology images 18 , 19 .…”

Section: Introductionmentioning

confidence: 99%

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Polarized hyperspectral microscopic imaging system for enhancing the visualization of collagen fibers and head and neck squamous cell carcinoma

Zhou,

Ma,

Mubarak

et al. 2024

J. Biomed. Opt.

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Polarized hyperspectral microscopes with the capability of full Stokes vector imaging have potential for many biological and medical applications.Aim: The aim of this study is to investigate polarized hyperspectral imaging (PHSI) for improving the visualization of collagen fibers, which is an important biomarker related to tumor development, and improving the differentiation of normal and tumor cells on pathologic slides.Approach: We customized a polarized hyperspectral microscopic imaging system comprising an upright microscope with a motorized stage, two linear polarizers, two liquid crystal variable retarders (LCVRs), and a compact SnapScan hyperspectral camera. The polarizers and LCVRs worked in tandem with the hyperspectral camera to acquire polarized hyperspectral images, which were further used to calculate four Stokes vectors: S0, S1, S2, and S3. Synthetic RGB images of the Stokes vectors were generated for the visualization of cellular components in PHSI images. Regions of interest of collagen, normal cells, and tumor cells in the synthetic RGB images were selected, and spectral signatures of the selected components were extracted for comparison. Specifically, we qualitatively and quantitatively investigated the enhanced visualization and spectral characteristics of dense fibers and sparse fibers in normal stroma tissue, fibers accumulated within tumors, and fibers accumulated around tumors.Results: By employing our customized polarized hyperspectral microscope, we extract the spectral signatures of Stokes vector parameters of collagen as well as of tumor and normal cells. The measurement of Stokes vector parameters increased the image contrast of collagen fibers and cells in the slides. Conclusions:With the spatial and spectral information from the Stokes vector data cubes (S0, S1, S2, and S3), our PHSI microscope system enhances the visualization of tumor cells and tumor microenvironment components, thus being beneficial for pathology and oncology.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Polarized hyperspectral microscopic imaging system for enhancing the visualization of collagen fibers and head and neck squamous cell carcinoma

Zhou,

Ma,

Mubarak

et al. 2024

J. Biomed. Opt.

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show abstract

“…Zhang et al [12] used a deep learning network and microhyperspectral images (HSI) to help identify precancerous lesions of gastric cancer (PLGC) and the diagnostic accuracy to 96.59%. Ma et al [13] demonstrated that the morphological and spectral information contribute to SCC nuclei differentiation and that the spectral information within hyperspectral images could improve classification performance. Hyperspectral images and RGB images of the histologic slides with the same field of view were obtained and registered.…”

Section: Introductionmentioning

confidence: 99%

Research for accurate auxiliary diagnosis of lung cancer based on intracellular fluorescent fingerprint information

Tian

Zhu

et al. 2023

Journal of Biophotonics

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The distinctions in pathological types and genetic subtypes of lung cancer have a direct impact on the choice of treatment choices and clinical prognosis in clinical practice. This study used pathological histological sections of surgically removed or biopsied tumor tissue from 36 patients. Based on a small sample size, millions of spectral data points were extracted to investigate the feasibility of employing intracellular fluorescent fingerprint information to diagnose the pathological types and mutational status of lung cancer. The intracellular fluorescent fingerprint information revealed the EGFR gene mutation characteristics in lung cancer, and the area under the curve (AUC) value for the optimal model was 0.98. For the classification of lung cancer pathological types, the macro average AUC value for the ensemble‐learning model was 0.97. Our research contributes new idea for pathological diagnosis of lung cancer and offers a quick, easy, and accurate auxiliary diagnostic approach.

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“…Light matter interaction results in numerous phenomena like absorption, refraction, reflection, transmission, scattering and much more depending on various factors like the sample under consideration, the mode in which we are operating etc. Interaction of light with biological specimens is also wavelength-dependent due to the refractive index variations across them hence multiwavelength information is beneficial over single wavelengths as it comes up with better sensitivity, accuracy and understanding [20][21][22]. Many multi-wavelength optical polarization approaches have already been proposed with various polarization imaging modalities like Stokes, Mueller and Jones matrix imaging [23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Multispectral polarization microscopy of different stages of human oral tissue: A polarization study

Mann,

Thapa,

Nayyar

et al. 2023

Journal of Biophotonics

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Many optical techniques have been used in various diagnostics and biomedical applications since a decade and polarization imaging is one of the non‐invasive and label free optical technique to investigate biological samples making it an important tool in diagnostics, biomedical applications. We report a multispectral polarization‐based imaging of oral tissue by utilizing a polarization microscope system with a broadband‐light source. Experiments were performed on oral tissue samples and multispectral Stokes mapping was done by recording a set of intensity images. Polarization‐based parameters like degree of polarization, angle of fast axis, retardation and linear birefringence have been retrieved. The statistical moments of these polarization components have also been reported at multiples wavelengths. The polarimetric properties of oral tissue at different stages of cancer have been analyzed and significant changes from normal to pre‐cancerous lesions to the cancerous are observed in linear birefringence quantification as (1.7± 0.1) ×10‐3, (2.5± 0.2) ×10‐3 and (3.3±0.2) ×10‐3 respectively.This article is protected by copyright. All rights reserved.

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Automatic detection of head and neck squamous cell carcinoma on histologic slides using hyperspectral microscopic imaging

Cited by 15 publications

References 47 publications

Polarized hyperspectral microscopic imaging system for enhancing the visualization of collagen fibers and head and neck squamous cell carcinoma

Polarized hyperspectral microscopic imaging system for enhancing the visualization of collagen fibers and head and neck squamous cell carcinoma

Research for accurate auxiliary diagnosis of lung cancer based on intracellular fluorescent fingerprint information

Multispectral polarization microscopy of different stages of human oral tissue: A polarization study

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