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Background EUS-guided FNA is one of the few techniques that can obtain cells and tissue from the liver and pancreas. However, the technique remains vulnerable to poor specimen quality and sampling error. Objective To evaluate the ability of a high-resolution microendoscope (HRME) to visualize the cellular and architectural features of normal and malignant liver and pancreatic tissue ex vivo, to assess the ability of endosonographers to identify normal and neoplastic tissue by using HRME images, and to demonstrate preliminary technical feasibility of in vivo HRME imaging via EUS fine-needle puncture (FNP). Design Ex vivo pilot feasibility study in human tissue; in vivo swine model. Setting Two academic medical centers. Patients Co-registered HRME images and biopsies were obtained from surgically resected hepatic and pancreatic tissues from 44 patients. Intervention Images were divided into training (12 images) and test (80 images) sets containing a range of normal and pathologic conditions for each organ. After viewing the training sets, 9 endosonographers attempted to distinguish malignant tissue from normal or benign lesions in the test sets, each of which contained 40 unique images with individual diagnoses from pathology. Main Outcome Measurements Image acquisition feasibility, ex vivo and in vivo. Ability of endosonographers to recognize features of normal/benign or malignant tissue from the liver and pancreas. Results Overall, the 9 endosonographers achieved median accuracy figures of 85% in the liver and 90% in the pancreas. The endosonographers with prior experience in reading HRME images achieved accuracy rates between 90% and 95%. Technical feasibility of HRME imaging through a 19-gauge EUS-FNP needle was demonstrated in an in vivo swine model. Limitations Ex vivo study. Conclusion High-resolution microendoscopy allows real-time imaging of cellular-level morphology and tissue architecture in the liver and pancreas. The technique appears to have a short learning curve, after which endosonographers achieved high accuracy rates in distinguishing malignant tissue from normal and benign pathology in both organs. Translating this imaging platform to the in vivo setting appears technically feasible.

Introduction Pathologists currently diagnose breast lesions through histologic assessment, which requires fixation and tissue preparation. The diagnostic criteria used to classify breast lesions are qualitative and subjective, and inter-observer discordance has been shown to be a significant challenge in the diagnosis of selected breast lesions, particularly for borderline proliferative lesions. Thus, there is an opportunity to develop tools to rapidly visualize and quantitatively interpret breast tissue morphology for a variety of clinical applications. Methods Toward this end, we acquired images of freshly excised breast tissue specimens from a total of 34 patients using confocal fluorescence microscopy and proflavine as a topical stain. We developed computerized algorithms to segment and quantify nuclear and ductal parameters that characterize breast architectural features. A total of 33 parameters were evaluated and used as input to develop a decision tree model to classify benign and malignant breast tissue. Benign features were classified in tissue specimens acquired from 30 patients and malignant features were classified in specimens from 22 patients. Results The decision tree model that achieved the highest accuracy for distinguishing between benign and malignant breast features used the following parameters: standard deviation of inter-nuclear distance and number of duct lumens. The model achieved 81 % sensitivity and 93 % specificity, corresponding to an area under the curve of 0.93 and an overall accuracy of 90 %. The model classified IDC and DCIS with 92 % and 96 % accuracy, respectively. The cross-validated model achieved 75 % sensitivity and 93 % specificity and an overall accuracy of 88 %. Conclusions These results suggest that proflavine staining and confocal fluorescence microscopy combined with image analysis strategies to segment morphological features could potentially be used to quantitatively diagnose freshly obtained breast tissue at the point of care without the need for tissue preparation. Electronic supplementary material The online version of this article (doi:10.1186/s13058-015-0617-9) contains supplementary material, which is available to authorized users.

Background and Aims 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. Methods 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. Results 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%. Conclusions 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. (Clinical trial registration number: NCT01384227 and NCT02018367.)

Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is useful to obtain specimens from lesions underlying deep parts of the liver and spleen. However, the development of novel ancillary techniques must be explored to reduce the number of needle passes and potential adverse effects during this procedure. We conducted an animal study using a swine to demonstrate technical feasibility of in vivo cytological observation of liver and spleen using the high-resolution microendoscopy (HRME) system under EUS guidance. We successfully performed the study. No significant acute adverse events occurred during the procedure. The HRME system could obtain clear images representing cytology-level morphology of spleen and liver. Hence, it is found out that in vivo cytological observation of liver and spleen using the HRME system under EUS guidance is technically feasible.

This study introduces an approach for quantitative analysis of microendoscopic images to identify esophageal neoplasia. The approach quantifies morphologic parameters which distinguish esophageal neoplasia accurately in an independent validation set

This prospective pilot study evaluates the potential of high-resolution fiber optic microscopy (HRFM) to identify lymph node metastases in breast cancer patients. 43 lymph nodes were collected from 14 consenting breast cancer patients. Proflavine dye was topically applied to lymph nodes ex vivo to allow visualization of nuclei. 242 images were collected at 105 sites with confirmed histopathologic diagnosis. Quantitative statistical features were calculated from images, assessed with one-way ANOVA, and were used to develop a classification algorithm with the goal of objectively discriminating between normal and metastatic tissue. A classification algorithm using mean image intensity and skewness achieved sensitivity of 79% (27/34) and specificity of 77% (55/71). This study demonstrates the technical feasibility and diagnostic potential of HRFM with fluorescent contrast in the ex vivo evaluation of lymph nodes from breast cancer patients.

Oral cancer is a significant health problem in the USA and throughout the world. Most oral cancer patients are diagnosed at a late stage, when treatment is less successful and treatment-associated morbidity is more severe. A number of new diagnostic aids to conventional oral examination have recently been introduced to assist in the early detection of oral neoplasia. In particular, autofluorescence imaging has emerged as a promising adjunctive technique to improve early identification of oral premalignant lesions. Direct visual inspection of tissue autofluorescence has shown encouraging results in high-prevalence populations, but the technique requires subjective interpretation and depends on the visual recognition skills of the examiner. Capturing and analyzing digital fluorescence images can reduce subjectivity and potentially improve sensitivity of detection of precancerous changes. Recent studies of wide-field autofluorescence imaging in low-prevalence populations suggest that benign lesions such as inflammation may give rise to false-positive results. High-resolution fluorescence imaging is a new modality that can be used in conjunction with wide-field imaging to improve specificity by imaging subcellular detail of neoplastic tissues. The combination of wide-field and high-resolution fluorescence imaging systems with automated image analysis should be investigated to maximize overall diagnostic performance for early detection of oral neoplasia.

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 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. Methods 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. 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 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. 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.

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.