Clement Leung

Robotic ICSI (Intracytoplasmic Sperm Injection)

This paper is the first report of robotic intracytoplasmic sperm injection (ICSI). ICSI is a clinical procedure performed worldwide in fertility clinics, requiring pick-up of a single sperm and insertion of it into an oocyte (i.e., egg cell). Since its invention 20 years ago, ICSI has been conducted manually by a handful of highly skilled embryologists; however, success rates vary significantly among clinics due to poor reproducibility and inconsistency across operators. We leverage our work in robotic cell injection to realize robotic ICSI and aim ultimately, to standardize how clinical ICSI is performed. This paper presents some of the technical aspects of our robotic ICSI system, including a cell holding device, motion control, and computer vision algorithms. The system performs visual tracking of single sperm, robotic immobilization of sperm, aspiration of sperm with picoliter volume, and insertion of sperm into an oocyte with a high degree of reproducibility. The system requires minimal human involvement (requiring only a few computer mouse clicks), and is human operator skill independent. Using the hamster oocyte-human sperm model in preliminary trials, the robotic system demonstrated a high success rate of 90.0% and survival rate of 90.7% (n = 120).

Three-Dimensional Rotation of Mouse Embryos

Research and clinical applications, such as microinjection and polar-body biopsy involve 3-D rotation of mammalian oocytes/embryos. In these cell manipulation tasks, the polar body of an embryo/oocyte must be made visible and properly oriented under optical microscopy. Cell rotation in conventional manual operation by skilled professionals is based on trial and error, such as through repeated vacuum aspiration and release. The randomness of this manual procedure, its poor reproducibility, and inconsistency across operators entail a systematic technique for automated, noninvasive, 3-D rotational control of single cells. This paper reports a system that tracks the polar body of mouse embryos in real time and controls multiple motion control devices to conduct automated 3-D rotational control of mouse embryos. Experimental results demonstrated the systems capability for polar-body orientation with a high success rate of 90%, an accuracy of 1.9, and an average speed of 22.8 s/cell (versus averagely 40 s/cell in manual operation).

Automated Sperm Immobilization for Intracytoplasmic Sperm Injection

Sperm immobilization is a requisite step in intracytoplasmic sperm injection (ICSI). Conventionally, sperm immobilization is performed manually, which entails long training hours and stringent skills. Manual sperm immobilization also has the limitation of low success rates and poor reproducibility due to human fatigue and skill variations across operators. This paper presents a system for fully automated sperm immobilization to eliminate limitations in manual operation. Integrating computer vision and motion control algorithms, the automated system is able to visually track a sperm and control a micropipette to immobilize the sperm. A robust sperm tail tracking algorithm is developed to locate the optimal position on the sperm tail for sperm immobilization. The system demonstrates: 1) an average sperm tail tracking error of 0.95 μm; 2) a sperm tail visual tracking success rate of 96%; 3) a sperm immobilization success rate of 88.2% (based on 1000 trials); and 4) a speed of 6-7 s per successful immobilization.

Controlled Aspiration and Positioning of Biological Cells in a Micropipette

Manipulating single cells with a micropipette is the oldest, yet still a widely used technique. This paper discusses the aspiration of a single cell into a micropipette and positioning the cell accurately to a target position inside the micropipette. Due to the small volume of a single cell (picoliter) and nonlinear dynamics involved, these tasks have high skill requirements and are labor intensive in manual operation that is solely based on trial and error and has high failure rates. We present automated techniques in this paper for achieving these tasks via computer vision microscopy and closed-loop motion control. Computer vision algorithms were developed to detect and track a single cell outside and inside a micropipette for automated single-cell aspiration. A closed-loop robust controller integrating the dynamics of cell motion was designed to accurately and efficiently position the cell to a target position inside the micropipette. The system achieved high success rates of 98% for cell detection and 97% for cell tracking (n = 100). The automated system also demonstrated its capability of aspirating a single cell into a micropipette within 2 s (versus 10 s by highly skilled operators) and accurately positioning the cell inside the micropipette within 8 s (versus 25 s by highly skilled operators).

Robotic Adherent Cell Injection for Characterizing Cell–Cell Communication

Compared to robotic injection of suspended cells (e.g., embryos and oocytes), fewer attempts were made to automate the injection of adherent cells (e.g., cancer cells and cardiomyocytes) due to their smaller size, highly irregular morphology, small thickness (a few micrometers thick), and large variations in thickness across cells. This paper presents a robotic system for automated microinjection of adherent cells. The system is embedded with several new capabilities: automatically locating micropipette tips; robustly detecting the contact of micropipette tip with cell culturing surface and directly with cell membrane; and precisely compensating for accumulative positioning errors. These new capabilities make it practical to perform adherent cell microinjection truly via computer mouse clicking in front of a computer monitor, on hundreds and thousands of cells per experiment (versus a few to tens of cells as state of the art). System operation speed, success rate, and cell viability rate were quantitatively evaluated based on robotic microinjection of over 4000 cells. This paper also reports the use of the new robotic system to perform cell-cell communication studies using large sample sizes. The gap junction function in a cardiac muscle cell line (HL-1 cells), for the first time, was quantified with the system.

Detection and tracking of low contrast human sperm tail

Tracking sperm tail movement provides important information for clinical sperm research. It is also a crucial step for sperm immobilization in Intracytoplasmic Sperm Injection (ICSI). However, the low visibility of the sperm tail under optical microscopy, coupled with the sperm fast motility, render sperm tail identification and tracking challenging tasks to execute. This paper presents two approaches for sperm tail tracking: (1) the Maximum Intensity Region (MIR) algorithm, and (2) the Optical Flow (OF) algorithm. The algorithms were evaluated by calculating the Euclidean distance error between each tail tracking algorithms computed tail location and a users manual input via mouse click of the tails image location. Experimental results demonstrate that the OF algorithm and MIR algorithm are both capable of tracking the sperm tail with minimal error when viscous liquid is added to the sperm culture medium, which is the present clinical standard practice for slowing down sperm movement. The MIR algorithm outperforms the OF algorithm by 52% in tail tracking accuracy in situations where the viscous liquid is absent.

Automated cell manipulation: Robotic ICSI

This paper is the first report of robotic ICSI (intracytoplasmic sperm injection). ICSI is a clinical procedure performed worldwide in fertility clinics, requiring pick-up of a single sperm and insert it into oocyte (i.e., an egg cell). Since its invention 20 years ago, ICSI has been conducted manually by a handful of highly skilled embryologists; however, success rates vary significantly among clinics due to poor reproducibility and inconsistency across operators. We leverage our work in robotic cell injection to realize robotic ICSI and aim ultimately, to standardize how clinical ICSI is performed. This paper presents some of the technical aspects of our robotic ICSI system, including a cell holding device and motion control and computer vision algorithms. The system performs visual tracking of single sperm, robotic immobilization of sperm, aspiration of sperm with pico-liter volume, and insertion of sperm into an oocyte with a high degree of reproducibility. The system requires minimal human involvement (requiring only a few computer mouse clicking), and is human operator skill independent. Using the hamster oocyte-human sperm model in preliminary trials, the robotic system demonstrated a high success rate of 90.0% and survival rate of 90.7% (n=120).

Human Sperm Tracking, Analysis, and Manipulation

Sperm analysis and manipulation play a significant role in biology research and reproductive medicine (assisted reproductive technologies). This chapter reviews computer vision-based sperm tracking methods, sperm analysis techniques, and automated sperm manipulation. Based on computer vision tracking of sperm head and sperm tail, sperm motility can be quantified by calculating the sperm’s straight line velocity, curvilinear velocity, moving path linearity, and the sperm tail beating amplitude. Conventional computer-assisted sperm analysis (CASA) systems are capable of performing some of these tasks. Recent progress in this field provides additional, enhanced capabilities to biologists and clinical embryologists. This chapter also introduces recent progress in automating sperm manipulation procedures, including sperm immobilization, aspiration, and positioning inside a micropipette.

Automated microrobotic characterization of cell-cell communication

Most mammalian cells (e.g., cancer cells and cardiomyocytes) adhere to a culturing surface. Compared to robotic injection of suspended cells (e.g., embryos and oocytes), fewer attempts were made to automate the injection of adherent cells due to their smaller size, highly irregular morphology, small thickness (a few micrometers thick), and large variations in thickness across cells. This paper presents a recently developed robotic system for automated microinjection of adherent cells. The system is embedded with several new capabilities: automatically locating micropipette tips; robustly detecting the contact of micropipette tip with cell culturing surface and directly with cell membrane; and precisely compensating for accumulative positioning errors. These new capabilities make it practical to perform adherent cell microinjection truly via computer mouse clicking in front of a computer monitor, on hundreds and thousands of cells per experiment (vs. a few to tens of cells as state-of-the-art). System operation speed, success rate, and cell viability rate were quantitatively evaluated based on robotic microinjection of over 4,000 cells. This paper also reports the use of the new robotic system to perform cell-cell communication studies using large sample sizes. The gap junction function in a cardiac muscle cell line (HL-1 cells), for the first time, was quantified with the system.

Controlled positioning of biological cells inside a micropipette

Manipulating single cells with a micropipette is the oldest, yet still a widely used technique. This paper discusses the positioning of a single cell to a target position inside the micropipette after the cell is aspirated into the micropipette. Due to the small volume of a single cell (pico-liter) and nonlinear dynamics involved, this task has high skill requirements and is labor intensive in manual operation that is solely based on trial and error and has high failure rates. We present automated techniques in this paper for achieving this task. Computer vision algorithm was developed to track a single cell inside a micropipette for automated single-cell positioning. A closed-loop robust controller integrating the dynamics of cell motion was designed to accurately and efficiently position the cell to a target position inside the micropipette. The system achieved high success rates of 97% for cell tracking (n=100) and demonstrated its capability of accurately positioning a cell inside the micropipette within 8 seconds (vs. 25 seconds by highly skilled operators).