Real time optical vascular imaging a new method for the diagnosis and monitoring of oral diseases (Review Article).

INTRODUCTION Real Time Optical Vascular Imaging (RTOVI) is a technology developed in the Centre for Oral Clinical & Translational Sciences, within the Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, that allows rapid and preparation free, in-vivo imaging of the microvascular anatomy of the human oral cavity. Microvascular changes are known to be related to disease subtypes, in particular cancer. This makes in-vivo microvascular examination clinically valuable. However, at present there is lack of any analytical method able to objectively assess microvascular morphology images. DISCUSSION The assessment of microvascular morphology based on a subjective assessment was proven to be unreliable. There was a need to develop a software-based analysis for in-vivo microvascular images to support the validation of RTOVI. This paper reviews the authors work to develop and test an automated microvascular analysis method for RTOVI based on ImageJ based open source software. This allowed to determined which parameters offered a more robust mathematical representation of the microvascular anatomy of the gingival margin, such as the mean area per capillary and mean aspect ratio. However, in-vivo microvascular images from elsewhere within the oral cavity posed a bigger challenge to the analysis procedure due to the microvascular architectural complexity and poorer contrast. A customized version of (AA), a well-known ImageJ plugin used for the quantification of in-vitro microvascular images is under development in collaboration with the University of Paris Est Creteil. The aim of this work is to have an automated analysis method for in-vivo microvascular images able to offer a solid foundation for the diagnostic potential of RTOVI and subsequent clinical integration of this technology. CONCLUSION An automated analysis method for in-vivo microvascular images is paramount before any attempt to clinically validate RTOVI. Our initial work of testing a software based analysis demonstrated the effectiveness of some parameters, which is valuable for future work, and led us to move into a more sophisticated method involving customizing the AA software. This is an essential step, aiming to extend the potential of in-vivo microscopy with the clinical integration of RTOVI.