Developing the OpenFlexure Microscope towards medical use: technical and social challenges of developing globally accessible hardware for healthcare.

The OpenFlexure Microscope is an accessible, three-dimensional-printed robotic microscope, with sufficient image quality to resolve diagnostic features including parasites and cancerous cells. As access to lab-grade microscopes is a major challenge in global healthcare, the OpenFlexure Microscope has been developed to be manufactured, maintained and used in remote environments, supporting point-of-care diagnosis. The steps taken in transforming the hardware and software from an academic prototype towards an accepted medical device include addressing technical and social challenges, and are key for any innovation targeting improved effectiveness in low-resource healthcare. This article is part of the Theo Murphy meeting issue 'Open, reproducible hardware for microscopy'.

Deep-learning-based image super-resolution of an end-expandable optical fiber probe for application in esophageal cancer diagnostics.

Significance: Endoscopic screening for esophageal cancer (EC) may enable early cancer diagnosis and treatment. While optical microendoscopic technology has shown promise in improving specificity, the limited field of view (<1 mm) significantly reduces the ability to survey large areas efficiently in EC screening. Aim: To improve the efficiency of endoscopic screening, we propose a novel concept of end-expandable endoscopic optical fiber probe for larger field of visualization and for the first time evaluate a deep-learning-based image super-resolution (DL-SR) method to overcome the issue of limited sampling capability. Approach: To demonstrate feasibility of the end-expandable optical fiber probe, DL-SR was applied on simulated low-resolution microendoscopic images to generate super-resolved (SR) ones. Varying the degradation model of image data acquisition, we identified the optimal parameters for optical fiber probe prototyping. The proposed screening method was validated with a human pathology reading study. Results: For various degradation parameters considered, the DL-SR method demonstrated different levels of improvement of traditional measures of image quality. The endoscopists' interpretations of the SR images were comparable to those performed on the high-resolution ones. Conclusions: This work suggests avenues for development of DL-SR-enabled sparse image reconstruction to improve high-yield EC screening and similar clinical applications.

Use of topical methylene blue to image nuclear morphometry with a low-cost scanning darkfield microendoscope.

Significance: Fiber-optic microendoscopy is a promising approach to noninvasively visualize epithelial nuclear morphometry for early cancer and precancer detection. However, the broader clinical application of this approach is limited by a lack of topical contrast agents available for in vivo use. Aim: The aim of this study was to evaluate the ability to image nuclear morphometry in vivo with a novel fiber-optic microendoscope used together with topical application of methylene blue (MB), a dye with FDA approval for use in chromoendoscopy in the gastrointestinal tract. Approach: The low-cost, high-resolution microendoscope implements scanning darkfield imaging without complex optomechanical components by leveraging programmable illumination and the rolling shutter of the image sensor. We validate the integration of our system and MB staining for visualizing epithelial cell nuclei by performing ex vivo imaging on fresh animal specimens and in vivo imaging on healthy volunteers. Results: The results indicate that scanning darkfield imaging significantly reduces specular reflection and resolves epithelial nuclei with enhanced image contrast and spatial resolution compared to non-scanning widefield imaging. The image quality of darkfield images with MB staining is comparable to that of fluorescence images with proflavine staining. Conclusions: Our approach enables real-time microscopic evaluation of nuclear patterns and has the potential to be a powerful noninvasive tool for early cancer detection.

Utility of a Low-Cost 3-D Printed Microscope for Evaluating Esophageal Biopsies.

In this manuscript we assessed the utility of a low-cost 3D printed microscope to evaluate esophageal biopsies. We conducted a comparative analysis between the traditional microscope and our 3-D printed microscope, utilizing a set of esophageal biopsy samples obtained from patients undergoing screening endoscopy. Two pathologists independently examined 30 esophageal biopsies by light microscopy and digital images obtained using a low-cost 3D printed microscope (Observer 1 and 2). The glass slide consensus diagnosis was compared to the findings of 2 additional pathologist who independently just reviewed the digital images (Observer 3 and 4). The intra-observer agreement was substantial to almost perfect for observer 1 (k:0.64) and 2 (k:0.84). All four observers had 100% sensitivity and negative predictive value, whereas specificity ranged from 59% to 100% and positive predictive value ranged from 21% to 100%. The PPV and specificity were lower for the two Observers (3 and 4) who just examined the digital images. Overall, our results suggest that telepathology may be used with high sensitivity and specificity, utilizing the pictures produced by our 3D-printed microscope.

Gambian Mothers Lack Obstetric Danger Sign Knowledge, But Educational Intervention Shows Promise.

Background: The Gambia has the 12th highest maternal mortality rate in the world, with 80% of deaths resulting from avoidable causes. Unawareness of pregnancy danger signs (DS) has been shown to be a barrier to seeking obstetric care, while app-based education intervention has shown promise. Objective: We aim to assess patient awareness of DS, identify barriers to awareness, and evaluate potential for implementing smartphone-based technologies for education. Methods: A cross-sectional semi-structured survey was administered to Gambian women (n = 100) across five hospitals/health centers. Data and informed consent were collected via an online survey portal. Analysis included bivariate analysis and descriptive statistics with p < 0.05 significance level. Recall of 0-2 DS per category was classified as "low" knowledge, 3-5 as "moderate" knowledge, and 6+ as "sufficient" knowledge. Cross-category recall was quantified for overall awareness level (0-6 = "low", 7-12 = "moderate", 13+ = "sufficient". N = 28 total DS). Findings: Although 75% of participants (n = 100) self-perceived "sufficient" knowledge of DS, the average recall was only two (SD = 2, n = 11) pregnancy DS, one labor and delivery DS (SD = 1, n = 8), and one postpartum DS (SD = 1, n = 9). Twenty-one women were unable to recall any danger signs. "Low" awareness was identified in 77% of women, while 23%, and 0% of women showed "moderate" and "sufficient" overall awareness, respectively. Education level was significantly correlated with overall danger sign recall (ρ(98) = .243, p = .015) and awareness level (ρ(98) = .265, p = .008). Monthly income was significantly correlated with awareness level (ρ(97) = .311, p = .002). Smartphone ownership was reported by 76% of women, and 97% expressed interest in using app-based video (94%) or provider (93%) teaching. Conclusions: Women had low knowledge of obstetric danger signs, and true awareness of danger signs was remarkably lower than self-perceived knowledge. However, patients exhibited proper healthcare-seeking behavior when danger signs arose. Findings suggest that video- or messaging-based education from local healthcare providers may be effective DS educational interventions.

Design and Evaluation of ScanCap: A Low-Cost, Reusable Tethered Capsule Endoscope with Blue-Green Illumination Imaging for Unsedated Screening and Early Detection of Barrett's Esophagus.

Esophageal carcinoma is the sixth-leading cause of cancer death worldwide. A precursor to esophageal adenocarcinoma (EAC) is Barrett's Esophagus (BE). Early-stage diagnosis and treatment of esophageal neoplasia (Barrett's with high-grade dysplasia/intramucosal cancer) increase the five-year survival rate from 10% to 98%. BE is a global challenge; however, current endoscopes for early BE detection are costly and require extensive infrastructure for patient examination and sedation. We describe the design and evaluation of the first prototype of ScanCap, a high-resolution optical endoscopy system with a reusable, low-cost tethered capsule, designed to provide high-definition, blue-green illumination imaging for the early detection of BE in unsedated patients. The tethered capsule (12.8 mm diameter, 35.5 mm length) contains a color camera and rotating mirror and is designed to be swallowed; images are collected as the capsule is retracted manually via the tether. The tether provides electrical power and illumination at wavelengths of 415 nm and 565 nm and transmits data from the camera to a tablet. The ScanCap prototype capsule was used to image the oral mucosa in normal volunteers and ex vivo esophageal resections; images were compared to those obtained using an Olympus CV-180 endoscope. Images of superficial capillaries in intact oral mucosa were clearly visible in ScanCap images. Diagnostically relevant features of BE, including irregular Z-lines, distorted mucosa, and dilated vasculature, were clearly visible in ScanCap images of ex vivo esophageal specimens.

Deployment and assessment of a deep learning model for real-time detection of anal precancer with high frame rate high-resolution microendoscopy.

Anal cancer incidence is significantly higher in people living with HIV as HIV increases the oncogenic potential of human papillomavirus. The incidence of anal cancer in the United States has recently increased, with diagnosis and treatment hampered by high loss-to-follow-up rates. Novel methods for the automated, real-time diagnosis of AIN 2+ could enable "see and treat" strategies, reducing loss-to-follow-up rates. A previous retrospective study demonstrated that the accuracy of a high-resolution microendoscope (HRME) coupled with a deep learning model was comparable to expert clinical impression for diagnosis of AIN 2+ (sensitivity 0.92 [P = 0.68] and specificity 0.60 [P = 0.48]). However, motion artifacts and noise led to many images failing quality control (17%). Here, we present a high frame rate HRME (HF-HRME) with improved image quality, deployed in the clinic alongside a deep learning model and evaluated prospectively for detection of AIN 2+ in real-time. The HF-HRME reduced the fraction of images failing quality control to 4.6% by employing a high frame rate camera that enhances contrast and limits motion artifacts. The HF-HRME outperformed the previous HRME (P < 0.001) and clinical impression (P < 0.0001) in the detection of histopathologically confirmed AIN 2+ with a sensitivity of 0.91 and specificity of 0.87.