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Octopi: Open configurable high-throughput imaging platform for infectious disease diagnosis in the field

Hongquan Li, Hazel Soto-Montoya, Maxime Voisin, Lucas Fuentes Valenzuela, View ORCID ProfileManu Prakash
doi: https://doi.org/10.1101/684423
Hongquan Li
1Department of Electrical Engineering, Stanford University, Stanford, CA
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Hazel Soto-Montoya
2Department of Bioengineering, Stanford University, Stanford, CA
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Maxime Voisin
3Department of Computer Science, Stanford University, Stanford, CA
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Lucas Fuentes Valenzuela
1Department of Electrical Engineering, Stanford University, Stanford, CA
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Manu Prakash
3Department of Computer Science, Stanford University, Stanford, CA
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  • ORCID record for Manu Prakash
  • For correspondence: manup@stanford.edu
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Abstract

Access to quantitative, robust, yet affordable diagnostic tools is necessary to reduce global infectious disease burden. Manual microscopy has served as a bedrock for diagnostics with wide adaptability, although at a cost of tedious labor and human errors. Automated robotic microscopes are poised to enable a new era of smart field microscopy but current platforms remain cost prohibitive and largely inflexible, especially for resource poor and field settings. Here we present Octopi, a low-cost ($250-$500) and reconfigurable autonomous microscopy platform capable of automated slide scanning and correlated bright-field and fluorescence imaging. Being highly modular, it also provides a framework for new disease-specific modules to be developed. We demonstrate the power of the platform by applying it to automated detection of malaria parasites in blood smears. Specifically, we discovered a spectral shift on the order of 10 nm for DAPI-stained Plasmodium falciparum malaria parasites. This shift allowed us to detect the parasites with a low magnification (equivalent to 10x) large field of view (2.56 mm2) module. Combined with automated slide scanning, real time computer vision and machine learning-based classification, Octopi is able to screen more than 1.5 million red blood cells per minute for parasitemia quantification, with estimated diagnostic sensitivity and specificity exceeding 90% at parasitemia of 50/ul and 100% for parasitemia higher than 150/l. With different modules, we further showed imaging of tissue slice and sputum sample on the platform. With roughly two orders of magnitude in cost reduction, Octopi opens up the possibility of a large robotic microscope network for improved disease diagnosis while providing an avenue for collective efforts for development of modular instruments.

One sentence summary We developed a low-cost ($250-$500) automated imaging platform that can quantify malaria parasitemia by scanning 1.5 million red blood cells per minute.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 27, 2019.
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Octopi: Open configurable high-throughput imaging platform for infectious disease diagnosis in the field
Hongquan Li, Hazel Soto-Montoya, Maxime Voisin, Lucas Fuentes Valenzuela, Manu Prakash
bioRxiv 684423; doi: https://doi.org/10.1101/684423
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Octopi: Open configurable high-throughput imaging platform for infectious disease diagnosis in the field
Hongquan Li, Hazel Soto-Montoya, Maxime Voisin, Lucas Fuentes Valenzuela, Manu Prakash
bioRxiv 684423; doi: https://doi.org/10.1101/684423

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