Multimodal Optical Imaging for Detection of Cervical Neoplasia

Abstract

Despite being the most preventable cancer, cervical cancer remains the third leading cause of cancer death worldwide. Over 85% of cervical cancer incidence and mortality occurs in low-resource countries where screening programs for early detection are either inadequate or unavailable. In the developed world, where screening programs are well organized, incidence and mortality rates are greatly reduced. Recent advances in optical imaging have the potential to enable cervical cancer screening at the point-of-care, even in the hands of less experienced providers. High performance optical imaging systems can be constructed at relatively low cost, and image analysis can be automated; thus, these technologies may provide a way to bridge the gap to cervical cancer screening for developing countries. This work focuses on the design, construction, and clinical testing of a novel multimodal optical imaging (combination of wide-field imaging and high-resolution) for early detection of cervical neoplasia. The Multimodal Digital Imager (MDI) acquires in vivo images of cervical tissue in fluorescence, narrow band reflectance, and orthogonal polarized reflectance modes using multiple illumination wavelengths. The High Resolution Microendoscope (HRME) was used to interrogate clinically suspicious areas with subcellular spatial resolution, revealing changes in nuclear to cytoplasmic area ratio. In vivo image data from the wide-field system was combined with image data from a high- resolution microendoscope (HRME) in order to test the effectiveness of the multimodal optical imaging in discriminating between cervical neoplasia and non-neoplastic. Multimodal optical imaging coupled with computer aided diagnostic achieved a sensitivity of 82% and specificity of 85% for discriminating cervical neoplastic from non-neoplastic This work has demonstrated that multimodal optical imaging; combination of wide-field and high-resolution optical imaging of the cervix can assist in the detection of cervical neoplasia and can be implemented effectively in a low-resource setting.