Imperial College London
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ProfessorBobBrown

Faculty of Medicine, Department of Surgery & Cancer

Senior Research Investigator
 
 
 
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Contact

 

+44 (0)20 7594 1804b.brown Website

 
 
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Assistant

 

Ms Sophie Lions +44 (0)20 7594 2792

 
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Location

 

1 007Institute of Reproductive and Developmental BiologyHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Phelps:2018:10.1038/s41416-018-0048-3,
author = {Phelps, DL and Balog, J and Gildea, LF and Bodai, Z and El-Bahrawy, MA and Speller, AVM and Rosini, F and Kudo, H and McKenzie, JS and Brown, R and Takats, Z and Ghaem-Maghami, S},
doi = {10.1038/s41416-018-0048-3},
journal = {British Journal of Cancer},
pages = {1349--1358},
title = {The surgical intelligent knife distinguishes normal, borderline and malignant gynaecological tissues using rapid evaporative ionisation mass spectrometry (REIMS)},
url = {http://dx.doi.org/10.1038/s41416-018-0048-3},
volume = {118},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundSurvival from ovarian cancer (OC) is improved with surgery, but surgery can be complex and tumour identification, especially for borderline ovarian tumours (BOT), is challenging. The Rapid Evaporative Ionisation Mass Spectrometric (REIMS) technique reports tissue histology in real-time by analysing aerosolised tissue during electrosurgical dissection.MethodsAerosol produced during diathermy of tissues was sampled with the REIMS interface. Histological diagnosis and mass spectra featuring complex lipid species populated a reference database on which principal component, linear discriminant and leave-one-patient-out cross-validation analyses were performed.ResultsA total of 198 patients provided 335 tissue samples, yielding 3384 spectra. Cross-validated OC classification vs separate normal tissues was high (97·4% sensitivity, 100% specificity). BOT were readily distinguishable from OC (sensitivity 90.5%, specificity 89.7%). Validation with fresh tissue lead to excellent OC detection (100% accuracy). Histological agreement between iKnife and histopathologist was very good (kappa 0.84, P < 0.001, z = 3.3). Five predominantly phosphatidic acid (PA(36:2)) and phosphatidyl-ethanolamine (PE(34:2)) lipid species were identified as being significantly more abundant in OC compared to normal tissue or BOT (P < 0.001, q < 0.001).ConclusionsThe REIMS iKnife distinguishes gynaecological tissues by analysing mass-spectrometry-derived lipidomes from tissue diathermy aerosols. Rapid intra-operative gynaecological tissue diagnosis may improve surgical care when histology is unknown, leading to personalised operations tailored to the individual.
AU  - Phelps,DL
AU  - Balog,J
AU  - Gildea,LF
AU  - Bodai,Z
AU  - El-Bahrawy,MA
AU  - Speller,AVM
AU  - Rosini,F
AU  - Kudo,H
AU  - McKenzie,JS
AU  - Brown,R
AU  - Takats,Z
AU  - Ghaem-Maghami,S
DO  - 10.1038/s41416-018-0048-3
EP  - 1358
PY  - 2018///
SN  - 0007-0920
SP  - 1349
TI  - The surgical intelligent knife distinguishes normal, borderline and malignant gynaecological tissues using rapid evaporative ionisation mass spectrometry (REIMS)
T2  - British Journal of Cancer
UR  - http://dx.doi.org/10.1038/s41416-018-0048-3
UR  - http://hdl.handle.net/10044/1/56732
VL  - 118
ER  -
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