We have optimized the design and imaging procedures, to clearly resolve the malaria parasite in Giemsa-stained thin blood smears, using simple low-cost cellphone-based microscopy with oil immersion. The microscope uses a glass ball as the objective and the phone camera as the tube lens. Our optimization includes the optimal choice of the ball lens diameter, the size and the position of the aperture diaphragm, and proper application of immersion, to achieve diagnostic capacity in a wide field of view. The resulting system is potentially applicable to low-cost in-the-field optical diagnostics of malaria as it clearly resolves micron-sized features and allows for analysis of parasite morphology in the field of 50 × 50 μm, and parasite detection in the field of at least 150 × 150 μm.

Conventional microscopy is the standard procedure for the diagnosis of schistosomiasis, despite its limited sensitivity, reliance on skilled personnel, and the fact that it is error prone. Here, we report the performance of the innovative (semi-)automated Schistoscope 5.0 for optical digital detection and quantification of Schistosoma haematobium eggs in urine, using conventional microscopy as the reference standard. At baseline, 487 participants in a rural setting in Nigeria were assessed, of which 166 (34.1%) tested S. haematobium positive by conventional microscopy. Captured images from the Schistoscope 5.0 were analyzed manually (semiautomation) and by an artificial intelligence (AI) algorithm (full automation). Semi- and fully automated digital microscopy showed comparable sensitivities of 80.1% (95% confidence interval [CI]: 73.2–86.0) and 87.3% (95% CI: 81.3–92.0), but a significant difference in specificity of 95.3% (95% CI: 92.4–97.4) and 48.9% (95% CI: 43.3–55.0), respectively. Overall, estimated egg counts of semi- and fully automated digital microscopy correlated significantly with the egg counts of conventional microscopy (r = 0.90 and r = 0.80, respectively, P < 0.001), although the fully automated procedure generally underestimated the higher egg counts. In 38 egg positive cases, an additional urine sample was examined 10 days after praziquantel treatment, showing a similar cure rate and egg reduction rate when comparing conventional microscopy with semiautomated digital microscopy. In this first extensive field evaluation, we found the semiautomated Schistoscope 5.0 to be a promising tool for the detection and monitoring of S. haematobium infection, although further improvement of the AI algorithm for full automation is required.

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We have shown that the maximum achievable resolution of in-line lensless holographic microscope is limited by aliasing and, for collimated illumination, can not exceed the camera pixel size. This limit can be achieved only when the optimal conditions on spatial and temporal coherence state of the illumination are satisfied. The expressions defining the configuration, delivering maximum resolution with given spatial and temporal coherence of the illumination are obtained. The validity of these conditions is confirmed experimentally.

We present a simple method for the diagnosis of urinary schistosomiasis using an in-line lensless holographic microscope combined with flow cytometry technique. Using simple image processing algorithms and binary image classifier, our system provides automated detection of Schistosoma haematobium eggs in infected urine samples. Registered hologram is reconstructed by applying backpropagation from sensor to sample plane and reconstructed image is automatically analysed for the presence of S. haematobium eggs. Designed for use in a resource-poor laboratory setting, our proposed method has been implemented using a Raspberry Pi computer. From pre-clinical test performed with human urine samples spiked with S. haematobium eggs (approximately 200 eggs per 12 ml of urine), we achieved a sensitivity and specificity of 50.6% and 98.6% respectively. Our proposed method requires no complex sample preparation methods making the system simple to operate and useable in point-of-care diagnosis of urinary schistosomiasis.This method can be optimized to complement existing diagnostic procedures for the detection of S. haematobium eggs and can be deployed to inaccessible remote areas.

Temperature-drift-immune wavelength meter based on an integrated micro-ring resonator Taballione, C.; Agbana, Tope; Vdovin, Gleb; Hoekman, M; Wevers, L.; Kalkman, Jeroen; Verhaegen, Michel; van der Slot, P.J.M.; Boller, KJ ABSTRACTWe present an integrated optical wavelength meter based on a Si 3 N 4 /SiO 2 micro ring resonator (operating over a free spectral range of ≈ 2.6 nm) whose output response is immune to temperature changes. The wavelength meter readout is performed by a neural network and a non-linear optimization algorithm. This novel approach ensures a high wavelength estimation precision (≈ 50 pm). We observe a long-term reproducibility of the wavelength meter response over a time interval of one week. We investigate the influence of the ambient temperature on the estimated wavelength. We observe an immunity of the displayed output wavelength to temperature changes of up to several degrees. The temperature-drift immunity appears to be caused by deviations from the theoretically expected (perfect) transmission function of a ring resonator, i.e., caused by deviations that are usually undesired in spectroscopic devices.

Diagnosis of soil-transmitted helminth (STH) and schistosome infections relies largely on conventional microscopy which has limited sensitivity, requires highly trained personnel and is error-prone. Rapid advances in miniaturization of optical systems, sensors and processors have enhanced research and development of digital and automated microscopes suitable for the detection of these diseases in resource-limited settings. While some studies have reported proof-of-principle results, others have evaluated the performance of working prototypes in field settings. The extensive commercialization of these innovative devices has, however, not yet been achieved. This review provides an overview of recent publications (2010–2022) on innovative field applicable optical devices which can be used for the diagnosis of STH and schistosome infections. Using an adapted technology readiness level (TRL) scale taking into account the WHO target product profile (TPP) for these diseases, the developmental stages of the devices were ranked to determine the readiness for practical applications in field settings. From the reviewed 18 articles, 19 innovative optical devices were identified and ranked. Almost all of the devices (85%) were ranked with a TRL score below 8 indicating that, most of the devices are not ready for commercialization and field use. The potential limitations of these innovative devices were discussed. We believe that the outcome of this review can guide the end-to-end development of automated digital microscopes aligned with the WHO TPP for the diagnosis of STH and schistosome infections in resource-limited settings.

Schistosomiasis is a treatable and preventable neglected tropical disease of Public Health importance affecting over 200 million people worldwide while Nigeria is one of the high burden countries. Currently, available diagnostic tests are cumbersome, low in sensitivity and not field-adaptable given the high skills required that are not available in the rural settings where the diseases are majorly prevalent. There is an urgent need for an easy to use automated diagnostic device to replace the current gold standard, the human-operated microscope. Many promising automated diagnostic technologies are under development. However, a good understanding of the real needs within the local healthcare context is crucial in order to develop and implement a new health diagnostic device. Too often, there is a mismatch between what is needed and what is developed. A target product profile can guide the R&D process in matching with the needs in the local healthcare context. The goal of this project is to combine gaps in the healthcare system and needs from stakeholders with technological possibilities in order to develop a target product profile for a diagnostic device for S. haematobium for specific healthcare scenarios in Nigeria.