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The intelligent knife (iKnife) and its intraoperative diagnostic advantage for the treatment of cervical disease
- Source :
- Proceedings of the National Academy of Sciences of the United States of America
- Publication Year :
- 2020
- Publisher :
- Proceedings of the National Academy of Sciences, 2020.
-
Abstract
- Significance Clearance of surgical margins in early cervical cancer prevents the need for adjuvant chemoradiation and associated morbidity and allows fertility preservation. Clearance of disease is also crucial in the surgical management of local recurrence of cervical tumors with exenterative surgery. In this study intelligent knife technology was able to discriminate healthy from abnormal lesions on the cervix with high accuracy, highlighting the potential to improve intraoperative management of women treated surgically for cervical cancer and, as a result, patient outcomes. While pilot experiments in vivo are encouraging, accuracy remains to be validated in larger patient cohorts. Future studies could also explore whether this technology could be used for management of cervical preinvasive disease.<br />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.
- Subjects :
- Medical Sciences
cervical cancer
RADICAL TRACHELECTOMY
SURGERY
medicine.medical_treatment
Uterine Cervical Neoplasms
Mass Spectrometry
0302 clinical medicine
Medicine
Papillomaviridae
iKnife
IN-VIVO
Cervical cancer
REIMS
0303 health sciences
Univariate analysis
Multidisciplinary
biology
Discriminant Analysis
Margins of Excision
Iknife
Biological Sciences
Middle Aged
CANCER
3. Good health
Multidisciplinary Sciences
Chemistry
030220 oncology & carcinogenesis
Physical Sciences
Science & Technology - Other Topics
Female
RADIOTHERAPY
Adult
LOOP EXCISION
medicine.medical_specialty
fertility preservation
Urology
Cervical intraepithelial neoplasia
Sensitivity and Specificity
Gas Chromatography-Mass Spectrometry
03 medical and health sciences
BIOLOGICAL TISSUES
Humans
TRANSFORMATION ZONE
Cervical Intraepithelial Neoplasia
Aged
030304 developmental biology
Science & Technology
IDENTIFICATION
business.industry
Papillomavirus Infections
Cancer
Gold standard (test)
3126 Surgery, anesthesiology, intensive care, radiology
medicine.disease
biology.organism_classification
REAL-TIME ANALYSIS
Radiation therapy
business
Precancerous Conditions
Subjects
Details
- ISSN :
- 10916490 and 00278424
- Volume :
- 117
- Database :
- OpenAIRE
- Journal :
- Proceedings of the National Academy of Sciences
- Accession number :
- edsair.doi.dedup.....83c5fb0f1e9370832734661e4f49035a
- Full Text :
- https://doi.org/10.1073/pnas.1916960117