High-resolution Microendoscopy Images Research Articles

Automated In Vivo High-Resolution Imaging to Detect Human Papillomavirus-Associated Anal Precancer in Persons Living With HIV.

In the United States, the effectiveness of anal cancer screening programs has been limited by a lack of trained professionals proficient in high-resolution anoscopy (HRA) and a high patient lost-to-follow-up rate between diagnosis and treatment. Simplifying anal intraepithelial neoplasia grade 2 or more severe (AIN 2+) detection could radically improve the access and efficiency of anal cancer prevention. Novel optical imaging providing point-of-care diagnoses could substantially improve existing HRA and histology-based diagnosis. This work aims to demonstrate the potential of high-resolution microendoscopy (HRME) coupled with a novel machine learning algorithm for the automated, in vivo diagnosis of anal precancer. The HRME, a fiber-optic fluorescence microscope, was used to capture real-time images of anal squamous epithelial nuclei. Nuclear staining is achieved using 0.01% wt/vol proflavine, a topical contrast agent. HRME images were analyzed by a multitask deep learning network (MTN) that computed the probability of AIN 2+ for each HRME image. The study accrued data from 77 people living with HIV. The MTN achieved an area under the receiver operating curve of 0.84 for detection of AIN 2+. At the AIN 2+ probability cutoff of 0.212, the MTN achieved comparable performance to expert HRA impression with a sensitivity of 0.92 ( P = 0.68) and specificity of 0.60 ( P = 0.48) when using histopathology as the gold standard. When used in combination with HRA, this system could facilitate more selective biopsies and promote same-day AIN2+ treatment options by enabling real-time diagnosis.

High frame rate video mosaicking microendoscope to image large regions of intact tissue with subcellular resolution.

High-resolution microendoscopy (HRME) is a low-cost strategy to acquire images of intact tissue with subcellular resolution at frame rates ranging from 11 to 18 fps. Current HRME imaging strategies are limited by the small microendoscope field of view (∼0.5 mm2); multiple images must be acquired and reliably registered to assess large regions of clinical interest. Image mosaics have been assembled from co-registered frames of video acquired as a microendoscope is slowly moved across the tissue surface, but the slow frame rate of previous HRME systems made this approach impractical for acquiring quality mosaicked images from large regions of interest. Here, we present a novel video mosaicking microendoscope incorporating a high frame rate CMOS sensor and optical probe holder to enable high-speed, high quality interrogation of large tissue regions of interest. Microendoscopy videos acquired at >90 fps are assembled into an image mosaic. We assessed registration accuracy and image sharpness across the mosaic for images acquired with a handheld probe over a range of translational speeds. This high frame rate video mosaicking microendoscope enables in vivo probe translation at >15 millimeters per second while preserving high image quality and accurate mosaicking, increasing the size of the region of interest that can be interrogated at high resolution from 0.5 mm2 to >30 mm2. Real-time deployment of this high-frame rate system is demonstrated in vivo and source code made publicly available.

Cervical cancer prevention in El Salvador: A prospective evaluation of screening and triage strategies incorporating high-resolution microendoscopy to detect cervical precancer.

Cervical cancer remains a leading cause of cancer death for women in low- and middle-income countries. The goal of our study was to evaluate screening and triage strategies, including high-resolution microendoscopy (HRME), to detect cervical abnormalities concerning for precancer at the point of care. Women (n = 1824) were enrolled at the Instituto de Cáncer de El Salvador. All underwent screening by both human papillomavirus (HPV) testing using careHPV and visual inspection with acetic acid (VIA). Screen-positives, along with 10% of screen-negatives, were invited to return for a follow-up examination that included triage with VIA, colposcopy and HRME imaging. Biopsies were taken of any abnormalities identified. If no abnormalities were identified, then the worst scoring site by HRME was biopsied. The sensitivities of HPV testing and VIA to screen for cervical intraepithelial neoplasia Grade 2 or more severe diagnoses (CIN2+) were 82.1% and 75% (P = .77), while the specificities were 90.4% and 80.9% (P < .001), respectively. The sensitivities of VIA, colposcopy and HRME as triage tests for CIN2+ were 82.1%, 82.1% and 71.4%, respectively (P ≥ .38). HRME had a significantly higher specificity (66.7%) than VIA (51.9%) (P < .001) and colposcopy (53.3%) (P < .001). When evaluating different theoretical screening and triage strategies, screening with HPV testing followed by triage with HRME would result in more women receiving appropriate care (97%) compared to screening with VIA (75%) or HPV alone (90%). Our findings demonstrate that screening with HPV is superior to VIA, and that triage with HRME imaging increases the specificity of detecting CIN2+ at the point of care in a low-resource setting.

Algorithm to quantify nuclear features and confidence intervals for classification of oral neoplasia from high-resolution optical images.

.Purpose: In vivo optical imaging technologies like high-resolution microendoscopy (HRME) can image nuclei of the oral epithelium. In principle, automated algorithms can then calculate nuclear features to distinguish neoplastic from benign tissue. However, images frequently contain regions without visible nuclei, due to biological and technical factors, decreasing the data available to and accuracy of image analysis algorithms.Approach: We developed the nuclear density-confidence interval (ND-CI) algorithm to determine if an HRME image contains sufficient nuclei for classification, or if a better image is required. The algorithm uses a convolutional neural network to exclude image regions without visible nuclei. Then the remaining regions are used to estimate a confidence interval (CI) for the number of abnormal nuclei , a feature used by a previously developed algorithm (called the ND algorithm), to classify images as benign or neoplastic. The range of the CI determines whether the ND-CI algorithm can classify an image with confidence, and if so, the predicted category. The ND and ND-CI algorithm were compared by calculating their positive predictive value (PPV) and negative predictive value (NPV) on 82 oral biopsies with histopathologically confirmed diagnoses.Results: After excluding the images that could not be classified with confidence, the ND-CI algorithm had higher PPV (65% versus 59%) and NPV (78% versus 75%) than the ND algorithm.Conclusions: The ND-CI algorithm could improve the real-time classification of HRME images of the oral epithelium by informing the user if an improved image is required for diagnosis.

Automated software-assisted diagnosis of esophageal squamous cell neoplasia using high-resolution microendoscopy

High-resolution microendoscopy (HRME) is an optical biopsy technology that provides subcellular imaging of esophageal mucosa but requires expert interpretation of these histopathology-like images. We compared endoscopists with an automated software algorithm for detection of esophageal squamous cell neoplasia (ESCN) and evaluated the endoscopists' accuracy with and without input from the software algorithm. Thirteen endoscopists (6 experts, 7 novices) were trained and tested on 218 post-hoc HRME images from 130 consecutive patients undergoing ESCN screening/surveillance. The automated software algorithm interpreted all images as neoplastic (high-grade dysplasia, ESCN) or non-neoplastic. All endoscopists provided their interpretation (neoplastic or non-neoplastic) and confidence level (high or low) without and with knowledge of the software overlay highlighting abnormal nuclei and software interpretation. The criterion standard was histopathology consensus diagnosis by 2 pathologists. The endoscopists had a higher mean sensitivity (84.3%, standard deviation [SD] 8.0% vs 76.3%, P= .004), lower specificity (75.0%, SD 5.2% vs 85.3%, P< .001) but no significant difference in accuracy (81.1%, SD 5.2% vs 79.4%, P= .26) of ESCN detection compared with the automated software algorithm. With knowledge of the software algorithm, the specificity of the endoscopists increased significantly (75.0% to 80.1%, P= .002) but not the sensitivity (84.3% to 84.8%, P= .75) or accuracy (81.1% to 83.1%, P= .13). The increase in specificity was among novices (P= .008) but not experts (P= .11). The software algorithm had lower sensitivity but higher specificity for ESCN detection than endoscopists. Using computer-assisted diagnosis, the endoscopists maintained high sensitivity while increasing their specificity and accuracy compared with their initial diagnosis. Automated HRME interpretation would facilitate widespread usage in resource-poor areas where this portable, low-cost technology is needed.

Low-cost, high-resolution imaging for detecting cervical precancer in medically-underserved areas of Texas

ObjectiveCervical cancer rates in the United States have declined since the 1940's, however, cervical cancer incidence remains elevated in medically-underserved areas, especially in the Rio Grande Valley (RGV) along the Texas-Mexico border. High-resolution microendoscopy (HRME) is a low-cost, in vivo imaging technique that can identify high-grade precancerous cervical lesions (CIN2+) at the point-of-care. The goal of this study was to evaluate the performance of HRME in medically-underserved areas in Texas, comparing results to a tertiary academic medical center. MethodsHRME was evaluated in five different outpatient clinical settings, two in Houston and three in the RGV, with medical providers of varying skill and training. Colposcopy, followed by HRME imaging, was performed on eligible women. The sensitivity and specificity of traditional colposcopy and colposcopy followed by HRME to detect CIN2+ were compared and HRME image quality was evaluated. Results174 women (227 cervical sites) were included in the final analysis, with 12% (11% of cervical sites) diagnosed with CIN2+ on histopathology. On a per-site basis, a colposcopic impression of low-grade precancer or greater had a sensitivity of 84% and a specificity of 45% to detect CIN2+. While there was no significant difference in sensitivity (76%, p = 0.62), the specificity when using HRME was significantly higher than that of traditional colposcopy (56%, p = 0.01). There was no significant difference in HRME image quality between clinical sites (p = 0.77) or medical providers (p = 0.33). ConclusionsHRME imaging increased the specificity for detecting CIN2+ when compared to traditional colposcopy. HRME image quality remained consistent across different clinical settings.

Quantitative analysis of in vivo high-resolution microendoscopic images for the detection of neoplastic colorectal polyps.

.Colonoscopy is routinely performed for colorectal cancer screening but lacks the capability to accurately characterize precursor lesions and early cancers. High-resolution microendoscopy (HRME) is a low-cost imaging tool to visualize colorectal polyps with subcellular resolution. We present a computer-aided algorithm to evaluate HRME images of colorectal polyps and classify neoplastic from benign lesions. Using histopathology as the gold standard, clinically relevant features based on luminal morphology and texture are quantified to build the classification algorithm. We demonstrate that adenomatous polyps can be identified with a sensitivity and specificity of 100% and 80% using a two-feature linear discriminant model in a pilot test set. The classification algorithm presented here offers an objective framework to detect adenomatous lesions in the colon with high accuracy and can potentially improve real-time assessment of colorectal polyps.

Feasibility of high-resolution microendoscopy imaging for animal gastrointestinal mucosa

Objective To investigate the feasibility of high-resolution microendoscopy(HRME) imaging for animal gastrointestinal mucosa. Methods Mucosal tissues were harvested from the stomach, small intestine, and large intestine of Japanese big-ear white rabbits. The effects of HRME imaging of different locations such as the gastric antrum and fundus, small intestine and large intestine were observed, and those of different exposure time were compared.Accuracy of HRME imaging was compared with pathology. Results The specific tissues of the gastrointestinal mucosa could be clearly distinguished from the HRME images. In the superficial layer of the fundic mucosa, numerous closely arranged glands as well as oval or elongated branched openings of the gastric pits and linear peripheral cracks were visible; the nuclei were arranged regularly. In the superficial layer of the antral mucosa, irregular or tubular openings of the gastric pits and cracked glandular cavities were visible, with the cells surrounding the gastric pits regularly arranged and the nuclei small and densely distributed. In the superficial layer of the small intestine mucosa, stereoscopic thick-finger-shaped villi cluster was visible. The intervillous spaces were crack-like, and the surface was covered by regularly arranged reflective, absorptive cells. In the superficial layer of the large intestine mucosa, many regularly arranged daisy-like round crypts of uniform size, as well as reflective, goblet cells surrounding the crypt and the interval space between crypts were visible. When the exposure time increased, the nuclei became brighter. An excellent correlation was noted between the results of histologic examination and those obtained by using HRME. Conclusion HRME can produce accurate images of the animal gastrointestinal mucosae and may be a novel technique for further studies of human gastrointestinal pathology. Key words: Diagnostic imaging; Endoscopy, gastrointestinal; Microscopy; Feasibility studies; Feasibility studies

A Multimodal Optical Imaging Platform for the Early Detection of Gastric Malignancies

Abstract 14 We developed a novel multimodal video endoscope and evaluated its usefulness for the early detection of gastric neoplastic lesions. The imaging platform is a modified upper GI endoscope capable of white light imaging (WLI), widefield vital-dye fluorescence imaging (VFI) and high-resolution microendoscopy (HRME) in a single endoscopic insertion. A custom filter module is attached to the distal tip of the endoscope to enable VFI; HRME is performed by introducing a fiber optic probe through the endoscope working channel. Proflavine, a vital dye that stains nuclei is used to provide image contrast in both VFI and HRME. VFI images of proflavine stained tissue reveal the glandular patterns of the gastric mucosa, while HRME images reveal nuclear morphology with subcellular resolution. The performance of the platform was evaluated in a pilot study to image 35 patients with known or suspected gastric cancer undergoing either endoscopy or surgical resection. Patients were recruited at Mount Sinai Hospital, NY, and Hospital Evangelico in Siguatepeque, Honduras. For each patient, images were acquired with WLI, VFI and HRME sequentially during endoscopy. Images of neoplasia show disruption and effacement of glandular patterns. These alterations are visualized with enhanced contrast in VFI when compared to WLI; HRME images presenting the nuclear architecture at a subcellular level confirm these findings. Results suggest that this multimodal imaging platform can potentially enable a two-step protocol for early gastric cancer detection, wherein suspicious areas are red flagged with improved contrast using VFI, and then further imaged with HRME to confirm whether neoplasia is present based on changes in nuclear morphology. Given the convenient adaptation of the system design to other commercial endoscopes and the low cost of HRME (&lt; $2,500), the utility of this multimodal imaging platform should be further evaluated in in vivo studies and low-resource settings. AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST: Yubo Tang No relationship to disclose Jennifer Carns No relationship to disclose Timothy Quang No relationship to disclose Enrique M. Reina No relationship to disclose Susana Gonzalez No relationship to disclose Daniel G. Rosen Research Funding: Biotheragnostics Sharmila Anandasabapathy Honoraria: Medial Medical Rebecca R. Richards-Kortum Consulting or Advisory Role: Janssen Global Services Research Funding: Merck

A tablet-interfaced high-resolution microendoscope with automated image interpretation for real-time evaluation of esophageal squamous cell neoplasia.

In recent years high-resolution microendoscopy (HRME) has shown potential to improve screening for esophageal squamous cell neoplasia. 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. 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 invivo 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. The tablet-interfaced HRME demonstrated comparable imaging performance at a 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%, respectively, in the validation set compared with 84% and 95% achieved in the original study. The tablet-based HRME is a low-cost tool that provides quantitative diagnostic information to the endoscopist in real time. This could be especially beneficial in lower-resource settings for operators with less experience interpreting HRME images.

High-resolution microendoscopy: a point-of-care diagnostic for cervical dysplasia in low-resource settings.

Cervical cancer is the third leading cause of cancer-related death among women in low-to-middle income countries. Pap testing and pathological services are difficult to implement under these settings. Alternative techniques for the diagnosis of cervical precancer in these settings are needed to reduce the burden of the disease. The objective of this study was to evaluate the diagnostic accuracy of a low-cost, high-resolution microendoscope imaging system in identifying precancerous lesions of the cervix in vivo. A retrospective study of 59 patients undergoing colposcopy for an abnormal Pap test was performed at Hospital de Câncer de Barretos in Brazil. All patients underwent colposcopy as per standard of care, and acetowhite lesions were recorded. High-resolution microendoscopy (HRME) images were obtained from one colposcopically normal region and from all lesions observed on colposcopy. Biopsies of abnormal areas were obtained and reviewed by three independent, blinded pathologists and compared with HRME findings. The mean nuclear area and the median nuclear eccentricity were calculated from HRME images acquired from each site. A diagnostic algorithm to distinguish histopathologically diagnosed cervical intraepithelial neoplasias of grade 2 or more severe lesions (high grade) from less severe lesions (low grade) was developed using these parameters. A test of trend was used to analyze the relationship between HRME positivity and severity of histopathogical diagnosis. Fisher's exact test was used to analyze differences in HRME positivity between high-grade and low-grade lesions. Evaluable images were obtained from 108 of 143 discrete sites. Of these, 71 sites were colposcopically normal or low grade according to histopathology and 37 were diagnosed as high grade on the basis of histopathology. Using the mean nuclear area and the median nuclear eccentricity, HRME images from 59 colposcopically abnormal sites were classified as high grade or low grade with 92% sensitivity and 77% specificity compared with histopathological findings. Increasing HRME positivity showed a significant trend with increasing severity of diagnosis (Ptrend<0.001). We found a strong association (P<0.001) between HRME positivity and a histopathological diagnosis of cervical intraepithelial neoplasia of grade 2 or higher. HRME demonstrated an accurate in-situ diagnosis of high-grade dysplasia. In low-resource settings in which colposcopy and histopathology services are severely limited or unavailable, HRME may provide a low-cost, accurate method for diagnosis of cervical precancer without the need for biopsy, allowing for a single 'screen-and-treat' approach.

Quantitative analysis of high-resolution microendoscopic images for diagnosis of neoplasia in patients with Barrett’s esophagus

Previous studies show that microendoscopic images can be interpreted visually to identify the presence of neoplasia in patients with Barrett's esophagus (BE), but this approach is subjective and requires clinical expertise. This study describes an approach for quantitative image analysis of microendoscopic images to identify neoplastic lesions in patients with BE. Images were acquired from 230 sites from 58 patients by using a fiberoptic high-resolution microendoscope during standard endoscopic procedures. Images were analyzed by a fully automated image processing algorithm, which automatically selected a region of interest and calculated quantitative image features. Image features were used to develop an algorithm to identify the presence of neoplasia; results were compared with a histopathology diagnosis. A sequential classification algorithm that used image features related to glandular and cellular morphology resulted in a sensitivity of 84% and a specificity of 85%. Applying the algorithm to an independent validation set resulted in a sensitivity of 88% and a specificity of 85%. This pilot study demonstrates that automated analysis of microendoscopic images can provide an objective, quantitative framework to assist clinicians in evaluating esophageal lesions from patients with BE. ( NCT01384227 and NCT02018367.).

High‐resolution microendoscope imaging of inverted papilloma and normal sinonasal mucosa: evaluation of interobserver concordance

High-resolution microendoscopy (HRME) enables real-time imaging of epithelial tissue. The utility of this novel imaging modality for inverted papilloma has not been previously described. This study examines the ability of otolaryngologists to differentiate between images of inverted papilloma and normal sinonasal mucosa obtained with a HRME. Inverted papilloma and normal sinonasal mucosa specimens were stained with a contrast agent, proflavine. HRME images were subsequently captured. Histopathological diagnosis was obtained for each sample. Quality-controlled images were used to assemble a training set. After reviewing the training images, 6 otolaryngologists without prior HRME experience reviewed and classified test images. Five samples of inverted papilloma and 2 normal sinonasal mucosa samples were collected. Four representative images from each specimen were used for the 28-image test set. The mean accuracy among all reviewers was 89.9% (95% confidence interval [CI], 84.3% to 94.0%). The sensitivity to correctly identify inverted papilloma was 86.7% (95% CI, 79.2% to 92.2%), and the specificity was 92.9% (95% CI, 89.0% to 100.0%). The Fleiss kappa interrater reliability score was 0.80 (95% CI, 0.70 to 0.89). Inverted papilloma and normal sinonasal mucosa have distinct HRME imaging characteristics. Otolaryngologists can be successfully trained to distinguish between inverted papilloma and normal sinonasal mucosa. HRME is a feasible tool for identification of inverted papilloma. By conducting future in vivo trials, HRME potentially may enable real-time surgical margin determination during surgical excision of inverted papilloma.

Quantitative evaluation of in vivo vital-dye fluorescence endoscopic imaging for the detection of Barrett's-associated neoplasia.

Current imaging tools are associated with inconsistent sensitivity and specificity for detection of Barrett's-associated neoplasia. Optical imaging has shown promise in improving the classification of neoplasia in vivo. The goal of this pilot study was to evaluate whether in vivo vital dye fluorescence imaging (VFI) has the potential to improve the accuracy of early-detection of Barrett's-associated neoplasia. In vivo endoscopic VFI images were collected from 65 sites in 14 patients with confirmed Barrett's esophagus (BE), dysplasia, oresophageal adenocarcinoma using a modular video endoscope and a high-resolution microendoscope(HRME). Qualitative image features were compared to histology; VFI and HRME images show changes in glandular structure associated with neoplastic progression. Quantitative image features in VFI images were identified for objective image classification of metaplasia and neoplasia, and a diagnostic algorithm was developed using leave-one-out cross validation. Three image features extracted from VFI images were used to classify tissue as neoplastic or not with a sensitivity of 87.8% and a specificity of 77.6% (AUC = 0.878). A multimodal approach incorporating VFI and HRME imaging can delineate epithelial changes present in Barrett's-associated neoplasia. Quantitative analysis of VFI images may provide a means for objective interpretation of BE during surveillance.

627 Analysis of High Resolution Microendoscopic Images for the Automated Diagnosis of Colon Neoplasia

The ability to distinguish adenomas from benign polyps during routine colonoscopy can be challenging. High-resolution microendoscopy (HRME) is an advanced optical imaging technique allowing subcellular imaging of the colorectal mucosa. This study aimed to develop quantitative HRME image analysis algorithms based on pathological and architectural features. In addition, it aimed to evaluate the automated classification algorithms performance to accurately categorize neoplastic (tubular adenoma, tubulovillous adenoma and cancer) and non-neoplastic (normal, hyperplastic) mucosa in the colon.

Quantitative Analysis of High-Resolution Microendoscopic Images for Diagnosis of Esophageal Squamous Cell Carcinoma

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 be interpreted readily 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. We performed an 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 at 1 hospital in the United States from May 2010 to October 2012. Biopsy specimens were collected from imaged sites (n= 375), and a consensus diagnosis was provided by 2 expert gastrointestinal pathologists and used as the standard. 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 the 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. 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.

High‐Resolution Microendoscope Images of Middle Ear Cholesteatoma and Surrounding Tissue: Evaluation of Interobserver Concordance

Investigate how accurately otolaryngologists could differentiate between images obtained with high-resolution microendoscopy (HRME) of ex vivo cholesteatoma specimens and surrounding middle ear epithelium. HRME images of surgically resected cholesteatoma and middle ear epithelium were obtained and otolaryngologists classified these images. Tertiary medical center. Resected cholesteatoma and middle ear epithelium were stained with a contrast agent, proflavine, and HRME images were captured. Specimens were sent for standard histopathology and compared with HRME images. Quality-controlled images were used to assemble a training set. After viewing training images, otolaryngologists without prior cholesteatoma HRME experience reviewed and classified test images. Ten cholesteatoma and 9 middle ear specimens were collected, of which 17 representative cholesteatoma and 19 middle ear epithelium images were extracted for a testing set. Qualitative analysis for concordance between HRME images and histological images yielded a strong correlation between modalities. The mean accuracy of all reviewers in correctly identifying images was 95% (95% confidence interval [CI], 92%-98%). The sensitivity to correctly detect cholesteatoma images was 98% (95% CI, 93%-100%), and the specificity was 92% (95% CI, 87%-97%). The Fleiss kappa interrater reliability score was 0.83, (95% CI, 0.77-0.89). Medical professionals can quickly be trained to accurately distinguish between HRME images of cholesteatoma and normal middle ear epithelium, both of which have distinct imaging characteristics. Real-time HRME optical imaging can potentially improve the results of otologic surgery by allowing for extirpation of cholesteatomas while eliminating residual disease.

Endoscopic ultrasound-assisted direct peritoneal visualization with a small-caliber scope: A proof of concept study in a swine model.

Background:Laparoscopic and natural orifice transluminal endoscopic surgery techniques can diagnose peritoneal findings that suggest tumor cell dissemination. However, they have not been incorporated into routine practice, mainly owing to their complexity. To develop a minimally invasive endoscopic technique for the diagnosis of peritoneal findings, we conducted feasibility study using an acute swine model.Materials and Methods:This study involved six domestic pigs. Trans-gastric access to the peritoneal cavity was performed utilizing an endoscopic ultrasound fine needle aspiration (EUS-FNA) technique. After dilation of the needle hole with a biliary dilatation catheter and balloon, a small-caliber scope was inserted into the peritoneal cavity. Peritoneal images were obtained with the scope and a high-resolution microendoscope (HRME). Main outcome measurements were technical feasibility and time needed to access the peritoneal cavity.Results:Direct visualization of the peritoneum was successful in all six pigs and gained access to the gross appearance of the peritoneal cavity. HRME imaging with topical contrast agent also obtained reasonable quality images representing nuclei of the peritoneal mesothelium. Average operation time from the initiation of EUS-FNA to acquiring peritoneal images was 26.5 min (range 15-40 min). Autopsy found no damage to the adjacent organs, and stomach wall defects were tightly closed with hemostasis clips.Conclusion:EUS-assisted direct peritoneal visualization with small-caliber scope is technically feasible. HRME may assist in the diagnosis of findings on the peritoneum.

Axial response of high-resolution microendoscopy in scattering media

High-resolution microendoscopy (HRME) uses epi-fluorescence imaging with a coherent fiber-optic bundle to enable in vivo examination of cellular morphology. While the HRME platform has recently gained popularity as a simple alternative to confocal endomicroscopy, the axial response of HRME in thick, scattering tissue has yet to be described quantitatively. These details are important because when analyzing images collected by HRME, out-of-focus light may affect the accuracy of quantitative parameters such as nuclear-to-cytoplasm ratio, which has been proposed as a diagnostic indicator of dysplasia or cancer. In this study we investigated the imaging properties of the HRME system by using phantoms simulating scattering tissue with fluorescently labeled nuclei. We directly compared HRME imaging with confocal endomicroscopy in phantoms and in vivo human tissue. HRME images defocused (deep) objects with apparent diameters and intensity levels that are in agreement with a simple geometric model. Out-of-focus nuclei contribute a relatively low, uniform background level to images which neither leads to the erroneous appearance of large nuclei from deep layers, nor prevents accurate imaging of superficial nuclei with high contrast.

High‐Resolution Microendoscope Images of Middle Ear Cholesteatoma and Surrounding Tissue: Evaluation of Interobserver Concordance

Objectives: High-resolution microendoscopy (HRME) has great potential to detect residual cholesteatoma in patients. This study investigated how accurately otolaryngologists could differentiate between images obtained with HRME of ex vivo cholesteatoma specimens and surrounding middle ear epithelium. Methods: Cholesteatoma and surrounding middle ear epithelium were resected from patients. Tissues were stained with a contrast agent, proflavine. The HRME was placed directly on each specimen, and images were captured. Specimens were sent for standard histopathology and were subsequently compared with HRME images. Images were evaluated for quality control, and a training set was assembled. After viewing training images, 8 otolaryngologists without prior cholesteatoma HRME experience reviewed and classified test images. Results: Ten cholesteatoma and 9 middle ear specimens were collected, of which 17 representative cholesteatoma and 19 middle ear epithelium images were extracted for a testing set. Qualitative analysis for concordance between HRME images and histological images yielded a strong correlation between modalities. The mean accuracy of all reviewers in correctly identifying images was 95% [95% confidence interval [CI]: 92, 98]. The sensitivity to correctly detect cholesteatoma images was 98% [95% CI: 93, 100], and the specificity was 92% [95% CI: 87, 97]. The Fleiss kappa inter-rater reliability score was 0.83 [95% CI: 0.77, 0.89]. Conclusions: Medical professionals can quickly be trained to accurately distinguish between HRME images of cholesteatoma and normal middle ear epithelium, both of which have distinct imaging characteristics. Real-time HRME optical imaging can potentially improve the results of otologic surgery by allowing for extirpation of cholesteatomas while eliminating residual disease.