In-vivo Detection of Cervical Cancer Lesions using Hyperspectral Colposcopy

In-vivo Detection of Cervical Cancer Lesions using Hyperspectral Colposcopy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article In-vivo Detection of Cervical Cancer Lesions using Hyperspectral Colposcopy Carlos Vega, Norberto Medina, Raquel Leon, Himar Fabelo, Alicia Martín, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8281102/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Cervical cancer originates from precursor lesions in the cervix, where early diagnosis is essential to avoid progression to invasive carcinoma. Today, lesion detection relies mainly on colposcopy, a highly operator-dependent procedure with considerable variability in accuracy, particularly among less-experienced clinicians. In this study, we present hyperspectral imaging-based approach for assisted colposcopy. We developed a custom hyperspectral colposcope covering 470–900 nm and conducted a 32-month clinical study including 116 patients and 245 hyperspectral images acquired during routine examinations. First, a dedicated algorithm automatically delineated the cervical region and segmented the tissue into ectocervix, endocervix and abnormal areas, achieving a macro F1-score of 0.84. Subsequently, two approaches were studied for pixel-wise lesion classification: a binary model for high-grade squamous intraepithelial lesion and invasive carcinoma versus healthy tissue, which achieved a mean F1-score of 0.74 on an independent test set; and a multiclass model for grading according to the Bethesda system, which showed lower generalization (F1-score=0.26) due to limited spectral resolution and spectral overlap. Overall, the results show the potential of hyperspectral colposcopy for non-invasive detection and delimitation of cervical lesions. Health sciences/Oncology/Cancer/Gynaecological cancer/Cervical cancer Health sciences/Oncology/Cancer/Cancer imaging Health sciences/Medical research/Biomarkers Health sciences/Health care/Medical imaging Full Text Additional Declarations There is NO Competing Interest. Supplementary Files nbeSupplementaryClassificationPaper.pdf Supplementary Figures Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8281102","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":561936625,"identity":"12af69b9-4f29-40cb-b533-107d8ffdce41","order_by":0,"name":"Carlos 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Today, lesion detection relies mainly on colposcopy, a highly operator-dependent procedure with considerable variability in accuracy, particularly among less-experienced clinicians. In this study, we present hyperspectral imaging-based approach for assisted colposcopy. We developed a custom hyperspectral colposcope covering 470–900 nm and conducted a 32-month clinical study including 116 patients and 245 hyperspectral images acquired during routine examinations. First, a dedicated algorithm automatically delineated the cervical region and segmented the tissue into ectocervix, endocervix and abnormal areas, achieving a macro F1-score of 0.84. Subsequently, two approaches were studied for pixel-wise lesion classification: a binary model for high-grade squamous intraepithelial lesion and invasive carcinoma versus healthy tissue, which achieved a mean F1-score of 0.74 on an independent test set; and a multiclass model for grading according to the Bethesda system, which showed lower generalization (F1-score=0.26) due to limited spectral resolution and spectral overlap. 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