Microscopy remains the gold standard for malaria diagnosis and treatment monitoring. However, manual microscopic examination of Giemsa stained blood smear, which has remained largely unchanged for more than a century since the invention of the technique, is labor intensive and prone to human errors. According to Slater, Hannah C., et al. Nature communications 10.1 (2019): 1433 (Figure 2), in several recent studies, the sensitivity of manual microscopy is found to be only 30% at parasitemia of 100 parasites per μl and 60% at 1000 parasites per μl, with large variations across clinics (these numbers should be compared to the perceived detection limit of expert microscopy, which is below 50 parasites per μl).
https://www.nature.com/articles/s41467-019-09441-1/figures/2: Estimated probability of detection by microscopy based on qPCR parasite density. Logistic regression model fits for ten study sites (a–j) with associated Bayesian 95% credible intervals (shaded area). Median model predictions for each dataset are presented in panel k and a pooled prediction (without the study-level random effect) is presented in panel l.
With the advances in consumer electronics, manufacturing and fast growing computational power that is available for a portable and battery powered computers, microscopy-based malaria diagnosis can be revolutionized by low-cost implementations of robotic microscopes with an optimized computation pipeline. Octopi is a focused effort towards realizing this paradigm shift.
Imaging the same region of a malaria positive patient blood smear with different octopi modules/magnifications and on a Nikon Ti2 microscope with a Prime 95B camera.
Scan of two malaria positive patient samples, and the associated scatter plots of extracted fluorescent spots.
Images of detected fluorescent spots from Octopi using the reversed cellphone lens imaging module and from Nikon Ti2 using a 20x/0.75 objective.
Spectral shift in DAPI-labeled parasites is further confirmed with a laser scanning confocal microscope. Excitation wavelength: 405 nm.
 Hongquan Li, Hazel Soto-Montoya, Maxime Voisin, Lucas Fuentes Valenzuela, and Manu Prakash. "Octopi: Open configurable high-throughput imaging platform for infectious disease diagnosis in the field." bioRxiv (2019): 684423. [link]
 Hongquan Li, Deepak Krishnamurthy, Ethan Li, Pranav Vyas, Nibha Akireddy, Chew Chai, Manu Prakash, "Squid: Simplifying Quantitative Imaging Platform Development and Deployment." bioRxiv [ link | website]
 Janie R. Byrum, Eric Waltari, Owen Janson, Syuan-Ming Guo, Jenny Folkesson, Bryant B. Chhun, Joanna Vinden, Ivan E. Ivanov, Marcus L. Forst, Hongquan Li, Adam G. Larson, Wesley Wu1, Cristina M. Tato, Krista M. McCutcheon, Michael J. Peluso, Timothy J. Henrich, Steven G. Deeks, Manu Prakash, Bryan Greenhouse, John E. Pak, Shalin B. Mehta. "multiSero: Open multiplex-ELISA platform for analyzing antibody responses to SARS-CoV-2 infection." bioRxiv [ link ]
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