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High contrast images of uterine tissue derived using Raman microspectroscopy with the empty modelling approach of multivariate curve resolution-alternating least squares

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High contrast images of uterine tissue derived using Raman microspectroscopy with the empty modelling approach of multivariate curve resolution-alternating least squares. / Patel, Imran I.; Trevisan, Julio; Evans, Geraint et al.
In: Analyst, Vol. 136, No. 23, 2011, p. 4950-4959.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Patel II, Trevisan J, Evans G, Llabjani V, Martin-Hirsch PL, Stringfellow HF et al. High contrast images of uterine tissue derived using Raman microspectroscopy with the empty modelling approach of multivariate curve resolution-alternating least squares. Analyst. 2011;136(23):4950-4959. doi: 10.1039/c1an15717e

Author

Patel, Imran I. ; Trevisan, Julio ; Evans, Geraint et al. / High contrast images of uterine tissue derived using Raman microspectroscopy with the empty modelling approach of multivariate curve resolution-alternating least squares. In: Analyst. 2011 ; Vol. 136, No. 23. pp. 4950-4959.

Bibtex

@article{4e0f4e3337a141f9aa23e24c5843c96c,
title = "High contrast images of uterine tissue derived using Raman microspectroscopy with the empty modelling approach of multivariate curve resolution-alternating least squares",
abstract = "Approaches that allow one to rapidly understand tissue structure and functionality in situ remain to be developed. Such techniques are required in many instances, including where there is a need to remove with a high degree of confidence positive tumour margins during surgical excision. As biological tissue has little contrast, gold standard confirmation of surgical margins is conventionally undertaken by histopathological diagnosis of tissue architecture via optical microscopy. Vibrational spectroscopy techniques, when coupled to sophisticated computational analyses, are capable of constructing bio-molecular contrast images of unstained tissue. To assess the relative applicability of a range of candidate algorithms to distinguish the in situ bio-molecular structures of a complex tissue, the empty modelling approach of multivariate curve resolution-alternating least squares (MCR-ALS) was compared to hierarchical cluster analysis (HCA) or principal component analysis (PCA). Such chemometric analyses were applied to Raman images of benign (tumour-adjacent) endometrium, stage I and stage II endometrioid cancer. Re-constructed images from the in situ bio-molecular tissue architectures highlighted features associated with glandular epithelium, stroma, glandular lumen and myometrium. Of the tested chemometric analyses, MCR-ALS provided the best bio-molecular contrast images, superior to those derived following HCA or PCA, with clear and defined margins of histological features. Iteratively-resolved spectra identified wavenumbers responsible for the contrast image. Wavenumbers 1234 cm(-1) (Amide III), 1390 cm(-1) (CH(3) bend), 1675 cm(-1) (Amide I/lipid), 1275 cm(-1) (Amide III), 918 cm(-1) (proline) and 936 cm(-1) (proline, valine and proteins) were responsible for generating the majority of the contrast within MCR-ALS-generated images. Applications of sophisticated computational analyses coupled with vibrational spectroscopy techniques have the potential to lend novel functionality insights into bio-molecular structures in vivo.",
keywords = "SPECTROSCOPY, MCR-ALS, CELLS, CANCER, ENDOMETRIAL CARCINOMA, HEAD",
author = "Patel, {Imran I.} and Julio Trevisan and Geraint Evans and Valon Llabjani and Martin-Hirsch, {Pierre L.} and Stringfellow, {Helen F.} and Martin, {Francis L.}",
year = "2011",
doi = "10.1039/c1an15717e",
language = "English",
volume = "136",
pages = "4950--4959",
journal = "Analyst",
issn = "0003-2654",
publisher = "Royal Society of Chemistry",
number = "23",

}

RIS

TY - JOUR

T1 - High contrast images of uterine tissue derived using Raman microspectroscopy with the empty modelling approach of multivariate curve resolution-alternating least squares

AU - Patel, Imran I.

AU - Trevisan, Julio

AU - Evans, Geraint

AU - Llabjani, Valon

AU - Martin-Hirsch, Pierre L.

AU - Stringfellow, Helen F.

AU - Martin, Francis L.

PY - 2011

Y1 - 2011

N2 - Approaches that allow one to rapidly understand tissue structure and functionality in situ remain to be developed. Such techniques are required in many instances, including where there is a need to remove with a high degree of confidence positive tumour margins during surgical excision. As biological tissue has little contrast, gold standard confirmation of surgical margins is conventionally undertaken by histopathological diagnosis of tissue architecture via optical microscopy. Vibrational spectroscopy techniques, when coupled to sophisticated computational analyses, are capable of constructing bio-molecular contrast images of unstained tissue. To assess the relative applicability of a range of candidate algorithms to distinguish the in situ bio-molecular structures of a complex tissue, the empty modelling approach of multivariate curve resolution-alternating least squares (MCR-ALS) was compared to hierarchical cluster analysis (HCA) or principal component analysis (PCA). Such chemometric analyses were applied to Raman images of benign (tumour-adjacent) endometrium, stage I and stage II endometrioid cancer. Re-constructed images from the in situ bio-molecular tissue architectures highlighted features associated with glandular epithelium, stroma, glandular lumen and myometrium. Of the tested chemometric analyses, MCR-ALS provided the best bio-molecular contrast images, superior to those derived following HCA or PCA, with clear and defined margins of histological features. Iteratively-resolved spectra identified wavenumbers responsible for the contrast image. Wavenumbers 1234 cm(-1) (Amide III), 1390 cm(-1) (CH(3) bend), 1675 cm(-1) (Amide I/lipid), 1275 cm(-1) (Amide III), 918 cm(-1) (proline) and 936 cm(-1) (proline, valine and proteins) were responsible for generating the majority of the contrast within MCR-ALS-generated images. Applications of sophisticated computational analyses coupled with vibrational spectroscopy techniques have the potential to lend novel functionality insights into bio-molecular structures in vivo.

AB - Approaches that allow one to rapidly understand tissue structure and functionality in situ remain to be developed. Such techniques are required in many instances, including where there is a need to remove with a high degree of confidence positive tumour margins during surgical excision. As biological tissue has little contrast, gold standard confirmation of surgical margins is conventionally undertaken by histopathological diagnosis of tissue architecture via optical microscopy. Vibrational spectroscopy techniques, when coupled to sophisticated computational analyses, are capable of constructing bio-molecular contrast images of unstained tissue. To assess the relative applicability of a range of candidate algorithms to distinguish the in situ bio-molecular structures of a complex tissue, the empty modelling approach of multivariate curve resolution-alternating least squares (MCR-ALS) was compared to hierarchical cluster analysis (HCA) or principal component analysis (PCA). Such chemometric analyses were applied to Raman images of benign (tumour-adjacent) endometrium, stage I and stage II endometrioid cancer. Re-constructed images from the in situ bio-molecular tissue architectures highlighted features associated with glandular epithelium, stroma, glandular lumen and myometrium. Of the tested chemometric analyses, MCR-ALS provided the best bio-molecular contrast images, superior to those derived following HCA or PCA, with clear and defined margins of histological features. Iteratively-resolved spectra identified wavenumbers responsible for the contrast image. Wavenumbers 1234 cm(-1) (Amide III), 1390 cm(-1) (CH(3) bend), 1675 cm(-1) (Amide I/lipid), 1275 cm(-1) (Amide III), 918 cm(-1) (proline) and 936 cm(-1) (proline, valine and proteins) were responsible for generating the majority of the contrast within MCR-ALS-generated images. Applications of sophisticated computational analyses coupled with vibrational spectroscopy techniques have the potential to lend novel functionality insights into bio-molecular structures in vivo.

KW - SPECTROSCOPY

KW - MCR-ALS

KW - CELLS

KW - CANCER

KW - ENDOMETRIAL CARCINOMA

KW - HEAD

U2 - 10.1039/c1an15717e

DO - 10.1039/c1an15717e

M3 - Journal article

VL - 136

SP - 4950

EP - 4959

JO - Analyst

JF - Analyst

SN - 0003-2654

IS - 23

ER -