High-throughput lensfree 3D tracking of human sperms reveals rare statistics of helical trajectories

Electrical Engineering Department, University of California, Los Angeles, CA 90095.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 09/2012; 109(40):16018-22. DOI: 10.1073/pnas.1212506109
Source: PubMed


Dynamic tracking of human sperms across a large volume is a challenging task. To provide a high-throughput solution to this important need, here we describe a lensfree on-chip imaging technique that can track the three-dimensional (3D) trajectories of > 1,500 individual human sperms within an observation volume of approximately 8-17 mm(3). This computational imaging platform relies on holographic lensfree shadows of sperms that are simultaneously acquired at two different wavelengths, emanating from two partially-coherent sources that are placed at 45° with respect to each other. This multiangle and multicolor illumination scheme permits us to dynamically track the 3D motion of human sperms across a field-of-view of > 17 mm(2) and depth-of-field of approximately 0.5-1 mm with submicron positioning accuracy. The large statistics provided by this lensfree imaging platform revealed that only approximately 4-5% of the motile human sperms swim along well-defined helices and that this percentage can be significantly suppressed under seminal plasma. Furthermore, among these observed helical human sperms, a significant majority (approximately 90%) preferred right-handed helices over left-handed ones, with a helix radius of approximately 0.5-3 μm, a helical rotation speed of approximately 3-20 rotations/s and a linear speed of approximately 20-100 μm/s. This high-throughput 3D imaging platform could in general be quite valuable for observing the statistical swimming patterns of various other microorganisms, leading to new insights in their 3D motion and the underlying biophysics.

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    • "Over the last few years, computational lensfree on-chip imaging has emerged and promises to be a versatile, cost-effective, field-portable and yet powerful biomedical imaging tool both in labs and at remote sites89. Based on digital in-line holography, this on-chip imaging technique was shown to be an alternative tool for various clinical and telemedicine applications, addressing diagnosis of diseases such as malaria10, automated cell counting11, water quality monitoring12, blood analysis13 as well as imaging cytometry141516. In this work, we demonstrate that lensfree on-chip imaging can provide a solution to wide-field cell motility tracking that can overcome many of the above outlined shortcomings of lens-based optical microscopy methods. "
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    ABSTRACT: Quantitative cell motility studies are necessary for understanding biophysical processes, developing models for cell locomotion and for drug discovery. Such studies are typically performed by controlling environmental conditions around a lens-based microscope, requiring costly instruments while still remaining limited in field-of-view. Here we present a compact cell monitoring platform utilizing a wide-field (24 mm(2)) lensless holographic microscope that enables automated single-cell tracking of large populations that is compatible with a standard laboratory incubator. We used this platform to track NIH 3T3 cells on polyacrylamide gels over 20 hrs. We report that, over an order of magnitude of stiffness values, collagen IV surfaces lead to enhanced motility compared to fibronectin, in agreement with biological uses of these structural proteins. The increased throughput associated with lensfree on-chip imaging enables higher statistical significance in observed cell behavior and may facilitate rapid screening of drugs and genes that affect cell motility.
    Scientific Reports 09/2014; 4:4717. DOI:10.1038/srep04717 · 5.58 Impact Factor
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    • "From the decade of the 1980 designing sperm imaging systems, tracking algorithms, and computerized analysis became center of attention broadly and valuable works were published in this area as well [2]-[4]. Some of them dealt with supplementary tools like acoustic device [3], piezo-electric device [5] and lens-free on-chip imaging technique [6] to provide 3D trajectory of sperm. Some others utilized optical tweezers to measure both sperm motility and energy [7] [8]. "
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    ABSTRACT: Sperm motility analysis has a particular place in male fertility diagnosis. Computerized sperm tracking has an important role in extracting sperm trajectory and measuring sperm’s dynamic features. Due to free movements of sperms in three dimensions, occlusion has remained a challenging problem in this area. This paper aims to present a robust single sperm tracking method being able to handle misdetections in sperm occlusion scenes. In this paper, a robust method of segmentation was utilized to provide the required measurements for a switchable weight particle filtering which was designed for single sperm tracking. In each frame, the target sperm was categorized in one of these three stages: before occlusion, occlusion, and after occlusion where the occlusion had been detected based on sperm’s physical characteristics. Depending on the target sperm stage, particles were weighted differently. In order to evaluate the algorithm, two groups of samples were studied where an expert had selected a single sperm of each sample to track manually and automatically. In the first group, the sperms with no occlusion along their trajectories were tracked to depict the general compatibility of the algorithm with sperm tracking. In the second group, the algorithm was applied on the sperms which had at least one occlusion during their path. The algorithm showed an accuracy of 95% on the first group and 86.66% on the second group which illustrate the robustness of the algorithm against occlusion.
    Advances in Sexual Medicine 07/2014; Vol. 4(No.3):42-54. DOI:10.4236/asm.2014.43008
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    • "In biology, it is established that the shapes of flagellar beat determine the moving path of a sperm cell [5], so retrieving the flagellar beat patterns, as well as the head trajectories, from image data will help shed new insight on the sperm motility assessment. This is especially true when analyzing complex, three-dimensional trajectories [6]. "
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    ABSTRACT: Sperm quality assessment plays an essential role in human fertility and animal breeding. Manual analysis is time-consuming and subject to intra- and inter-observer variability. To automate the analysis process, as well as to offer a means of statistical analysis that may not be achieved by visual inspection, we present a computational framework that tracks the heads and traces the tails for analyzing sperm motility, one of the most important attributes in semen quality evaluation. Our framework consists of 3 modules: head detection, head tracking, and flagellum tracing. The head detection module detects the sperm heads from the image data, and the detected heads are the inputs to the head tracking module for obtaining the head trajectories. Finally, a flagellum tracing algorithm is proposed to obtain the flagellar beat patterns. Our framework aims at providing both the head trajectories and the flagellar beat patterns for quantitatively assessing sperm motility. This distinguishes our work from other existing methods that analyze sperm motility based merely on the head trajectories. We validate our framework using two confo-cal microscopy image sequences of ram semen samples that were imaged at two different conditions, at which the sperms behave differently. The results show the effectiveness of our framework.
    IEEE International Symposium on Biomedical Imaging (ISBI); 04/2014
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