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Development of a Low-cost Smartphone-connected Digital Microscope.

ABSTRACT: Introduction:Modern light microscopes are available with built-in illuminator and facility of photomicrography. This enables the microscopy to be ready for telemedicine. However, resource-limited settings still find difficulty in procuring those microscopes. Aim:The aim of this study was to upgrade a light microscope to a smartphone-connected digital microscope with minimal cost to make it ready for telemedicine. Materials and Methods:A commercially available (price: ?389) Universal Serial Bus (USB) web camera was set on the eyepiece and fixed with the help of an aluminum sheet. Light emitting diodes (LEDs), covered with an optical diffuser, were set below the condenser. The camera was connected to an Android smartphone with an application for capturing image and video. Sixteen faculty members provided their opinion about the new device. Results:The smartphone-connected microscope was successfully used to focus and capture image and video of various slides. The images and videos were stored in the smartphone and shared via E-mail and other channels (e.g., WhatsApp and Telegram). This camera was also successfully connected to a laptop for projecting the real-time microscopic field on a screen. According to faculty members, focusing an object and capturing the image are the best features of the device; however, development of the device received lowest score. Conclusion:A light microscope was upgraded to telemedicine ready microscope with nominal cost and moderate effort. It can also be used in medical teachings as it can project real-time images of a slide under the microscope. As it is equipped with LEDs, powered by the same smartphone, it can be operated without daylight or during a power outage.

SUBMITTER: Mondal H

PROVIDER: S-EPMC7365514 | biostudies-literature | 2020 Apr-Jun

REPOSITORIES: biostudies-literature

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Development of a Low-cost Smartphone-connected Digital Microscope.

Mondal Himel H Mondal Shaikat S Saha Koushik K Roul Bichitrananda B

Journal of microscopy and ultrastructure 20191129 2

<h4>Introduction</h4>Modern light microscopes are available with built-in illuminator and facility of photomicrography. This enables the microscopy to be ready for telemedicine. However, resource-limited settings still find difficulty in procuring those microscopes.<h4>Aim</h4>The aim of this study was to upgrade a light microscope to a smartphone-connected digital microscope with minimal cost to make it ready for telemedicine.<h4>Materials and methods</h4>A commercially available (price: ₹389) ...[more]

PMID: 32766118

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Project description:Introduction: Accurate and rapid diagnostics paired with effective tracking and tracing systems are key to halting the spread of infectious diseases, limiting the emergence of new variants and to monitor vaccine efficacy. The current gold standard test (RT-qPCR) for COVID-19 is highly accurate and sensitive, but is time-consuming, and requires expensive specialised, lab-based equipment. Methods: Herein, we report on the development of a SARS-CoV-2 (COVID-19) rapid and inexpensive diagnostic platform that relies on a reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay and a portable smart diagnostic device. Automated image acquisition and an Artificial Intelligence (AI) deep learning model embedded in the Virus Hunter 6 (VH6) device allow to remove any subjectivity in the interpretation of results. The VH6 device is also linked to a smartphone companion application that registers patients for swab collection and manages the entire process, thus ensuring tests are traced and data securely stored. Results: Our designed AI-implemented diagnostic platform recognises the nucleocapsid protein gene of SARS-CoV-2 with high analytical sensitivity and specificity. A total of 752 NHS patient samples, 367 confirmed positives for coronavirus disease (COVID-19) and 385 negatives, were used for the development and validation of the test and the AI-assisted platform. The smart diagnostic platform was then used to test 150 positive clinical samples covering a dynamic range of clinically meaningful viral loads and 250 negative samples. When compared to RT-qPCR, our AI-assisted diagnostics platform was shown to be reliable, highly specific (100%) and sensitive (98-100% depending on viral load) with a limit of detection of 1.4 copies of RNA per µL in 30 min. Using this data, our CE-IVD and MHRA approved test and associated diagnostic platform has been approved for medical use in the United Kingdom under the UK Health Security Agency's Medical Devices (Coronavirus Test Device Approvals, CTDA) Regulations 2022. Laboratory and in-silico data presented here also indicates that the VIDIIA diagnostic platform is able to detect the main variants of concern in the United Kingdom (September 2023). Discussion: This system could provide an efficient, time and cost-effective platform to diagnose SARS-CoV-2 and other infectious diseases in resource-limited settings.

Project description:IntroductionA significant barrier to medical diagnostics in low-resource environments is the lack of medical care and equipment. Here we present a low-cost, cloud-connected digital microscope for applications at the point-of-care. We evaluate the performance of the device in the digital assessment of estrogen receptor-alpha (ER) expression in breast cancer samples. Studies suggest computer-assisted analysis of tumor samples digitized with whole slide-scanners may be comparable to manual scoring, here we study whether similar results can be obtained with the device presented.Materials and methodsA total of 170 samples of human breast carcinoma, immunostained for ER expression, were digitized with a high-end slide-scanner and the point-of-care microscope. Corresponding regions from the samples were extracted, and ER status was determined visually and digitally. Samples were classified as ER negative (<1% ER positivity) or positive, and further into weakly (1-10% positivity) and strongly positive. Interobserver agreement (Cohen's kappa) was measured and correlation coefficients (Pearson's product-momentum) were calculated for comparison of the methods.ResultsCorrelation and interobserver agreement (r = 0.98, p < 0.001, kappa = 0.84, CI95% = 0.75-0.94) were strong in the results from both devices. Concordance of the point-of-care microscope and the manual scoring was good (r = 0.94, p < 0.001, kappa = 0.71, CI95% = 0.61-0.80), and comparable to the concordance between the slide scanner and manual scoring (r = 0.93, p < 0.001, kappa = 0.69, CI95% = 0.60-0.78). Fourteen (8%) discrepant cases between manual and device-based scoring were present with the slide scanner, and 16 (9%) with the point-of-care microscope, all representing samples of low ER expression.ConclusionsTumor ER status can be accurately quantified with a low-cost imaging device and digital image-analysis, with results comparable to conventional computer-assisted or manual scoring. This technology could potentially be expanded for other histopathological applications at the point-of-care.

Dataset Information

Development of a Low-cost Smartphone-connected Digital Microscope.

Publications

Development of a Low-cost Smartphone-connected Digital Microscope.

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