If detected early, oral cancer is eminently curable. However, survival rates for oral cancer patients remain low, largely due to late stage diagnosis and subsequent difficulty of treatment. To improve clinicians’ ability to detect early disease and to treat advanced cancers, we developed a multi-modal optical imaging system (MMIS) to evaluate tissue in situ, at macroscopic and microscopic scales. The MMIS was used to measure anatomical 100 sites in 30 patients, correctly classifying 98% of pathologically confirmed normal tissue sites, and 95% of sites graded as moderate dysplasia, severe dysplasia, or cancer. When used alone, MMIS classification accuracy was 35% for sites determined by pathology as mild dysplasia. However, MMIS measurements correlated with expression of candidate molecular markers in 87% of sites with mild dysplasia. These findings support the ability of non-invasive multi-modal optical imaging to accurately identify neoplastic tissue and pre-malignant lesions. This in turn may have considerable impact on detection and treatment of patients with oral cancer and other epithelial malignancies.

BACKGROUND: Optical spectroscopy is a noninvasive technique with potential applications for diagnosis of oral dysplasia and early cancer. In this study, we evaluated the diagnostic performance of a depth-sensi-

Optical spectroscopy can provide useful diagnostic information about the morphological and biochemical changes related to the progression of precancer in epithelial tissue. As precancerous lesions develop, the optical properties of both the superficial epithelium and underlying stroma are altered; measuring spectral data as a function of depth has the potential to improve diagnostic performance. We describe a clinical spectroscopy system with a depth-sensitive, ball lens coupled fiber-optic probe for noninvasive in vivo measurement of oral autofluorescence and diffuse reflectance spectra. We report results of spectroscopic measurements from oral sites in normal volunteers and in patients with neoplastic lesions of the oral mucosa; results indicate that the addition of depth selectivity can enhance the detection of optical changes associated with precancer.

Background and Aims In recent years, high-resolution microendoscopy (HRME) has shown potential to improve screening for esophageal squamous cell neoplasia (ESCN). Furthering its utility in a clinical setting, especially in lower-resource settings, could be accomplished by reducing the size and cost of the system as well as incorporating the ability of real-time, objective feedback. This article describes a tablet-interfaced HRME with fully automated, real-time image analysis. Methods The performance of the tablet-interfaced HRME was assessed by acquiring images from the oral mucosa in a normal volunteer. An automated, real-time analysis algorithm was developed and evaluated using training, test, and validation images from a previous in vivo study of 177 patients referred for screening or surveillance endoscopy in China. The algorithm was then implemented in a tablet HRME that was used to obtain and analyze images from esophageal tissue in 3 patients. Images were displayed alongside the probability that the imaged region was neoplastic. Results The tablet-interfaced HRME demonstrated comparable imaging performance at lower cost compared with first-generation laptop-interfaced HRME systems. In a post-hoc quantitative analysis, the algorithm identified neoplasia with a sensitivity and specificity of 95% and 91% in the validation set, compared with 84% and 95% achieved in the original study. Conclusion The tablet-based HRME is a low-cost tool that provides quantitative diagnostic information to the endoscopist in real-time. This could especially be beneficial in lower-resource settings for operators with less experience interpreting HRME images.

Potentially premalignant oral epithelial lesions (PPOELs) are a group of clinically suspicious conditions, of which a small percentage will undergo malignant transformation. PPOELs are suboptimally diagnosed and managed under the current standard of care. Dysplasia is the most well-established marker to distinguish high-risk PPOELs from low-risk PPOELs, and performing a biopsy to establish dysplasia is the diagnostic gold standard. However, a biopsy is limited by morbidity, resource requirements, and the potential for underdiagnosis. Diagnostic adjuncts may help clinicians better evaluate PPOELs before definitive biopsy, but existing adjuncts, such as toluidine blue, acetowhitening, and autofluorescence imaging, have poor accuracy and are not generally recommended. Recently, in vivo microscopy technologies, such as high-resolution microendoscopy, optical coherence tomography, reflectance confocal microscopy, and multiphoton imaging, have shown promise for improving PPOEL patient care. These technologies allow clinicians to visualize many of the same microscopic features used for histopathologic assessment at the point of care.

Background & Aims High-resolution microendoscopy is an optical imaging technique with the potential to improve the accuracy of endoscopic screening for esophageal squamous neoplasia. Although these microscopic images can readily be interpreted by trained personnel, quantitative image analysis software could facilitate the use of this technology in low-resource settings. In this study we developed and evaluated quantitative image analysis criteria for the evaluation of neoplastic and non-neoplastic squamous esophageal mucosa. Methods We performed image analysis of 177 patients undergoing standard upper endoscopy for screening or surveillance of esophageal squamous neoplasia, using high-resolution microendoscopy, at 2 hospitals in China and 1 in the United States from May 2010 to October 2012. Biopsies were collected from imaged sites (n=375); a consensus diagnosis was provided by 2 expert gastrointestinal pathologists and used as the standard. Results Quantitative information from the high-resolution images was used to develop an algorithm to identify high-grade squamous dysplasia or invasive squamous cell cancer, based on histopathology findings. Optimal performance was obtained using mean nuclear area as the basis for classification, resulting in sensitivities and specificities of 93% and 92% in the training set, 87% and 97% in the test set, and 84% and 95% in an independent validation set, respectively. Conclusions High-resolution microendoscopy with quantitative image analysis can aid in the identification of esophageal squamous neoplasia. Use of software-based image guides may overcome issues of training and expertise in low-resource settings, allowing for widespread use of these optical biopsy technologies.

Reflectance spectroscopy is a promising technology for detection of epithelial precancer. Fiber-optic probes that selectively collect scattered light from both the epithelium and the underlying stroma are likely to improve diagnostic performance of in vivo reflectance spectroscopy by revealing diagnostic features unique to each layer. We present Monte Carlo models with which to evaluate fiber-optic probe geometries with respect to sampling depth and depth resolution. We propose a probe design that utilizes half-ball lens coupled source and detector fibers to isolate epithelial scattering from stromal scattering and hence to resolve spectral information from the two layers. The probe is extremely compact and can provide easy access to different organ sites.

A Monte Carlo model with site-specific input was used to predict depth-resolved fluorescence spectra from individual normal, inflammatory, and neoplastic oral sites. Our goal in developing this model was to provide a computational tool to study how the morphological characteristics of the tissue affect clinically measured spectra. Tissue samples from the measured sites were imaged using fluorescence confocal microscopy; autofluorescence patterns were measured as a function of depth and tissue sublayer for each individual site. These fluorescence distributions were used as input to the Monte Carlo model to generate predictions of fluorescence spectra, which were compared to clinically measured spectra on a site-by-site basis. A lower fluorescence intensity and longer peak emission wavelength observed in clinical spectra from dysplastic and cancerous sites were found to be associated with a decrease in measured fluorescence originating from the stroma or deeper fibrous regions, and an increase in the measured fraction of photons originating from the epithelium or superficial tissue layers. The simulation approach described here can be used to suggest an optical probe design that samples fluorescence at a depth that gives optimal separation in the spectral signal measured for benign, dysplastic and cancerous oral mucosa.