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<p>Cervical cancer remains a major global health concern, with a specially alarming incidence in younger women. Traditional detection techniques such as the Pap smear and colposcopy often lack sensitivity and specificity and are highly dependent on the experience of the gynaecologist. In response, this study proposes the use of Hyperspectral Imaging, a pioneering technology that combines traditional imaging with spectroscopy to provide detailed spatial and spectral information. Over a period of six-months, our custom-designed hyperspectral colposcope was used on 62 patients. The gathered data underwent a specialized preprocessing workflow using a PCA-based strategy for unsupervised segmentation of the cervical region. This process extracted spectral signatures from various tissue types, and our subsequent statistical analysis highlighted its ability to detect differences and alterations in the cervical tissue. This offers a promising avenue for improving the precision of cervical lesion diagnosis.</p>

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Feasibility study of hyperspectral colposcopy as a novel tool for detecting precancerous cervical lesions

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月4日

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  • Carlos Vega,
  • Norberto Medina,
  • Laura Quintana-Quintana,
  • Raquel Leon,
  • Himar Fabelo,
  • Jorge Rial,
  • Alicia Martín,
  • Gustavo M. Callico

摘要

Cervical cancer remains a major global health concern, with a specially alarming incidence in younger women. Traditional detection techniques such as the Pap smear and colposcopy often lack sensitivity and specificity and are highly dependent on the experience of the gynaecologist. In response, this study proposes the use of Hyperspectral Imaging, a pioneering technology that combines traditional imaging with spectroscopy to provide detailed spatial and spectral information. Over a period of six-months, our custom-designed hyperspectral colposcope was used on 62 patients. The gathered data underwent a specialized preprocessing workflow using a PCA-based strategy for unsupervised segmentation of the cervical region. This process extracted spectral signatures from various tissue types, and our subsequent statistical analysis highlighted its ability to detect differences and alterations in the cervical tissue. This offers a promising avenue for improving the precision of cervical lesion diagnosis.