The intelligent-Knife (i-Knife) and its intraoperative diagnostic advantage for the treatment of cervical disease
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Published version
Author(s)
Type
Journal Article
Abstract
Clearance of surgical margins in cervical cancer prevents the need for adjuvant chemoradiation and allows fertility preservation. In this study, we determined the capacity of the rapid evaporative ionization mass spectrometry (REIMS), also known as intelligent knife (iKnife), to discriminate between healthy, preinvasive, and invasive cervical tissue. Cervical tissue samples were collected from women with healthy, human papilloma virus (HPV) ± cervical intraepithelial neoplasia (CIN), or cervical cancer. A handheld diathermy device generated surgical aerosol, which was transferred into a mass spectrometer for subsequent chemical analysis. Combination of principal component and linear discriminant analysis and least absolute shrinkage and selection operator was employed to study the spectral differences between groups. Significance of discriminatory m/z features was tested using univariate statistics and tandem MS performed to elucidate the structure of the significant peaks allowing separation of the two classes. We analyzed 87 samples (normal = 16, HPV ± CIN = 50, cancer = 21 patients). The iKnife discriminated with 100% accuracy normal (100%) vs. HPV ± CIN (100%) vs. cancer (100%) when compared to histology as the gold standard. When comparing normal vs. cancer samples, the accuracy was 100% with a sensitivity of 100% (95% CI 83.9 to 100) and specificity 100% (79.4 to 100). Univariate analysis revealed significant MS peaks in the cancer-to-normal separation belonging to various classes of complex lipids. The iKnife discriminates healthy from premalignant and invasive cervical lesions with high accuracy and can improve oncological outcomes and fertility preservation of women treated surgically for cervical cancer. Larger in vivo research cohorts are required to validate these findings.
Date Issued
2020-03-31
Date Acceptance
2020-02-05
Citation
Proceedings of the National Academy of Sciences of USA, 2020, 117 (13), pp.7338-7346
ISSN
0027-8424
Publisher
National Academy of Sciences
Start Page
7338
End Page
7346
Journal / Book Title
Proceedings of the National Academy of Sciences of USA
Volume
117
Issue
13
Copyright Statement
© 2020 the Author(s). Published by PNAS.
This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
Sponsor
Imperial College Healthcare Charity
Imperial Health Charity
Imperial College Healthcare Charity
Imperial College Healthcare Charity
Genesis Research Trust
The British Society of Colposcopy Cervical Pathology
Imperial Confidence in Concept (ICiC) Award
Medical Research Council (MRC) Award
The Imperial Healthcare NHS Trust NIHR Biomedical Research Centre
Sigrid Jusélius Fellowship
Medical Research Council (MRC)
Imperial Health Charity
National Institute for Health Research
Imperial College Healthcare NHS Trust- BRC Funding
Identifier
https://www.pnas.org/content/117/13/7338
Grant Number
RF16/100015
P59319
P47907
P55549
P47773
PS2897
PS2857
P45272
P52483
MC_PC15028
RF16/100015
A173/A174
RDB01
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
REIMS
cervical cancer
mass spectrometry
iKnife
fertility preservation
REAL-TIME ANALYSIS
RADICAL TRACHELECTOMY
TRANSFORMATION ZONE
BIOLOGICAL TISSUES
LOOP EXCISION
IN-VIVO
CANCER
IDENTIFICATION
RADIOTHERAPY
SURGERY
REIMS
cervical cancer
fertility preservation
iKnife
mass spectrometry
Adult
Aged
Cervical Intraepithelial Neoplasia
Discriminant Analysis
Female
Gas Chromatography-Mass Spectrometry
Humans
Margins of Excision
Mass Spectrometry
Middle Aged
Papillomaviridae
Papillomavirus Infections
Precancerous Conditions
Sensitivity and Specificity
Uterine Cervical Neoplasms
Humans
Papillomaviridae
Papillomavirus Infections
Cervical Intraepithelial Neoplasia
Precancerous Conditions
Discriminant Analysis
Sensitivity and Specificity
Adult
Aged
Middle Aged
Uterine Cervical Neoplasms
Female
Mass Spectrometry
Gas Chromatography-Mass Spectrometry
Margins of Excision
Publication Status
Published
Date Publish Online
2020-03-16