Tissue discrimination in head and neck cancer using image fusion of IR and optical microscopy

Safaa Al Jedani; Caroline Smith; James Ingham; Conor Whitley; Barnaby Ellis; Asterios Triantafyllou; Philip Gunning; Peter Gardner; Janet Risk; Richard Shaw; Peter Weightman; Steve Barrett

doi:10.1039/D3AN00692A

Tissue discrimination in head and neck cancer using image fusion of IR and optical microscopy

Safaa Al Jedani, Caroline Smith, James Ingham, Conor Whitley, Barnaby Ellis, Asterios Triantafyllou, Philip Gunning, Peter Gardner, Janet Risk, Richard Shaw, Peter Weightman^*, Steve Barrett

^*Corresponding author for this work

CE - Academic & Research

Research output: Contribution to journal › Article › peer-review

Abstract

A regression-based fusion algorithm has been used to merge hyperspectral Fourier transform infrared (FTIR) data with an H&E image of oral squamous cell carcinoma metastases in cervical lymphoid nodal tissue. This provides insight into the success of the ratio of FTIR absorbances at 1252 cm−1 and 1285 cm−1 in discriminating between these tissue types. The success is due to absorbances at these two wavenumbers being dominated by contributions from DNA and collagen, respectively. A pixel-by-pixel fit of the fused spectra to the FTIR spectra of collagen, DNA and cytokeratin reveals the contributions of these molecules to the tissue at high spatial resolution.

Original language	English
Pages (from-to)	1489
Number of pages	1494
Journal	Analyst
Volume	148
Issue number	17
DOIs	https://doi.org/10.1039/D3AN00692A
Publication status	Published - 2023

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10.1039/D3AN00692A

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title = "Tissue discrimination in head and neck cancer using image fusion of IR and optical microscopy",

abstract = "A regression-based fusion algorithm has been used to merge hyperspectral Fourier transform infrared (FTIR) data with an H&E image of oral squamous cell carcinoma metastases in cervical lymphoid nodal tissue. This provides insight into the success of the ratio of FTIR absorbances at 1252 cm−1 and 1285 cm−1 in discriminating between these tissue types. The success is due to absorbances at these two wavenumbers being dominated by contributions from DNA and collagen, respectively. A pixel-by-pixel fit of the fused spectra to the FTIR spectra of collagen, DNA and cytokeratin reveals the contributions of these molecules to the tissue at high spatial resolution.",

author = "{Al Jedani}, Safaa and Caroline Smith and James Ingham and Conor Whitley and Barnaby Ellis and Asterios Triantafyllou and Philip Gunning and Peter Gardner and Janet Risk and Richard Shaw and Peter Weightman and Steve Barrett",

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doi = "10.1039/D3AN00692A",

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T1 - Tissue discrimination in head and neck cancer using image fusion of IR and optical microscopy

AU - Al Jedani, Safaa

AU - Smith, Caroline

AU - Ingham, James

AU - Whitley, Conor

AU - Ellis, Barnaby

AU - Triantafyllou, Asterios

AU - Gunning, Philip

AU - Gardner, Peter

AU - Risk, Janet

AU - Shaw, Richard

AU - Weightman, Peter

AU - Barrett, Steve

PY - 2023

Y1 - 2023

N2 - A regression-based fusion algorithm has been used to merge hyperspectral Fourier transform infrared (FTIR) data with an H&E image of oral squamous cell carcinoma metastases in cervical lymphoid nodal tissue. This provides insight into the success of the ratio of FTIR absorbances at 1252 cm−1 and 1285 cm−1 in discriminating between these tissue types. The success is due to absorbances at these two wavenumbers being dominated by contributions from DNA and collagen, respectively. A pixel-by-pixel fit of the fused spectra to the FTIR spectra of collagen, DNA and cytokeratin reveals the contributions of these molecules to the tissue at high spatial resolution.

AB - A regression-based fusion algorithm has been used to merge hyperspectral Fourier transform infrared (FTIR) data with an H&E image of oral squamous cell carcinoma metastases in cervical lymphoid nodal tissue. This provides insight into the success of the ratio of FTIR absorbances at 1252 cm−1 and 1285 cm−1 in discriminating between these tissue types. The success is due to absorbances at these two wavenumbers being dominated by contributions from DNA and collagen, respectively. A pixel-by-pixel fit of the fused spectra to the FTIR spectra of collagen, DNA and cytokeratin reveals the contributions of these molecules to the tissue at high spatial resolution.

U2 - 10.1039/D3AN00692A

DO - 10.1039/D3AN00692A

M3 - Article

SN - 0003-2654

VL - 148

SP - 1489

JO - Analyst

JF - Analyst

IS - 17

ER -

Tissue discrimination in head and neck cancer using image fusion of IR and optical microscopy

Abstract

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