Motility-based label-free detection of parasites in bodily fluids using holographic speckle analysis and deep learning

Parasitic infections constitute a major global public health issue. Existing screening methods that are based on manual microscopic examination often struggle to provide sufficient volumetric throughput and sensitivity to facilitate early diagnosis. Here, we demonstrate a motility-based label-free computational imaging platform to rapidly detect motile parasites in optically dense bodily fluids by utilizing the locomotion of the parasites as a specific biomarker and endogenous contrast mechanism. Based on this principle, a cost-effective and mobile instrument, which rapidly screens ~3.2 mL of fluid sample in three dimensions, was built to automatically detect and count motile microorganisms using their holographic time-lapse speckle patterns. We demonstrate the capabilities of our platform by detecting trypanosomes, which are motile protozoan parasites, with various species that cause deadly diseases affecting millions of people worldwide. Using a holographic speckle analysis algorithm combined with deep learning-based classification, we demonstrate sensitive and label-free detection of trypanosomes within spiked whole blood and artificial cerebrospinal fluid (CSF) samples, achieving a limit of detection of ten trypanosomes per mL of whole blood (~five-fold better than the current state-of-the-art parasitological method) and three trypanosomes per mL of CSF. We further demonstrate that this platform can be applied to detect other motile parasites by imaging Trichomonas vaginalis, the causative agent of trichomoniasis, which affects 275 million people worldwide. With its cost-effective, portable design and rapid screening time, this unique platform has the potential to be applied for sensitive and timely diagnosis of neglected tropical diseases caused by motile parasites and other parasitic infections in resource-limited regions. Scientists have developed a cost-effective and portable technology that uses three-dimensional holograms to detect parasites in human bodily fluids, providing a more sensitive technique for diagnosing diseases, without the need for chemical labeling. A major global health problem, parasitic infections affect billions of people around the world and can lead to severe illnesses and death. Some of the current screening techniques, however, use manual microscopic examinations that struggle to provide the sensitivity required for early diagnoses. Now, Aydogan Ozcan and colleagues from the University of California Los Angeles in the United States have developed a cost-effective and portable optical device that uses lensless time-resolved holographic speckle imaging combined with artificial intelligence to automatically detect rare parasites in bodily fluids. The device has the potential to perform rapid and early diagnoses of diseases caused by parasitic infections and could be used in developing countries.