Detection of Schistosoma haematobium using lensless imaging and flow cytometry, a proof of principle study

Temitope Agbana; Patrick Nijman; Max Hoeber; Derk van Grootheest; Angela van Diepen; Lisette van Lieshout; Jan-Carel Diehl; Michel Verhaegen; Gleb Vdovine

doi:10.1117/12.2545220

14 February 2020 Detection of Schistosoma haematobium using lensless imaging and flow cytometry, a proof of principle study

Temitope Agbana, Patrick Nijman, Max Hoeber, Derk van Grootheest, Angela van Diepen, Lisette van Lieshout, Jan-Carel Diehl, Michel Verhaegen, Gleb Vdovine

Author Affiliations +

Proceedings Volume 11247, Optical Diagnostics and Sensing XX: Toward Point-of-Care Diagnostics; 112470F (2020) https://doi.org/10.1117/12.2545220
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

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.

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Temitope Agbana, Patrick Nijman, Max Hoeber, Derk van Grootheest, Angela van Diepen, Lisette van Lieshout, Jan-Carel Diehl, Michel Verhaegen, and Gleb Vdovine "Detection of Schistosoma haematobium using lensless imaging and flow cytometry, a proof of principle study", Proc. SPIE 11247, Optical Diagnostics and Sensing XX: Toward Point-of-Care Diagnostics, 112470F (14 February 2020); https://doi.org/10.1117/12.2545220

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