5 Key Features of High Content Imaging Systems

High-content imaging (HCI), also known as high-content screening (HCS), is an automated form of multiplexed fluorescence microscopy. It leverages multi-parameter algorithms for unbiased analysis of images by computers, termed high content analysis (HCA). Since its inception, high-content imaging has become an essential approach for measuring changes arising from cellular events and studying their underlying mechanisms through multi-parametric visualization.

Being able to acquire high content data at the single-cell or subcellular level with extremely high throughput has expanded the range of high content screening applications inordinately. High content imaging platforms have subsequently evolved to encompass the ever-changing needs of different users. Greater flexibility is useful across the full spectrum of applications, while techniques like cell painting have proven vital in drug discovery and cytological profiling. More specific requirements include the needs of 2D, and 3D analysis based on fluorescence assays with complex cellular disease models and pharmacokinetic studies.

High-content imaging now plays an important analytical role in live-cell imaging and in screening labs. A wide range of HCI platforms are available to meet this growing berth of applications. Given their importance, selecting the right system is a critical process. How should you go about selecting the right high content imaging platform for your lab or project?

Here, we will discuss five key points for researchers to consider when choosing a new HCI/HCS system.

1. Image Quality

A high content imaging system is first and foremost a fluorescence microscope. As such, its image quality is the most important characteristic to consider.

High throughput is central to the purpose of high content imaging, but speed should never come at the expense of quality. Image sharpness and quality are substantially affected by the quality of autofocus technology and the optical path of the system.

Laser-based autofocus is a highly reliable focusing method for high content imaging systems. It ensures proper focus when scanning many samples at high speeds that is crucial for achieving good image sharpness and quality. These are vital qualities for achieving publication-grade images from which it is possible to extract reliable information. A sharp image enables accurate and reliable object identification and minimizes the number of errors in automated image analysis.

For system selection, it is important to ensure that the focusing algorithm is automatically adapted to the magnification (objective) used, since autofocus with high magnifications of 40X and above is challenging. Strict testing during equipment demonstrations should ensure the system does not fail at high magnification, particularly with high numerical aperture (NA) objectives.

Additionally, it is important to have a flexible definition of the autofocus procedure which can also be optimized for different magnifications. In some unique systems, the user can choose a process that maps the focal plane for a particular well in a multi-well plate using four separate autofocus points. Such a “fast” method saves autofocusing steps when imaging at multiple fields of view within a well. This can greatly reduce scanning times. 

Speed is affected by this multipoint option, especially compared to a “very fast” process which takes a single autofocus point at the center of a well. Yet it is still quicker than a “slow” process that performs autofocus for each individual field of view within the well. Autofocus options are more common at an intermediate magnification of around 10x, where the depth of field is still relatively large, compared to higher magnification where identifying the focal plane requires greater precision.

Image quality is the most important characteristic to consider when choosing a High Content Imaging system

2. Motion Accuracy

High content imaging involves rapid scanning of multi-well plates, often at multiple time points. When following dynamic processes and monitoring individual cells over time, a key essential factor is the accuracy of the scanner, i.e., motion repeatability.

A typical Eukaryote cell varies in size between tens to hundreds of micrometers across its widest point. When working with high NA and high magnification objectives,  typically 40X and above, it is important to make sure that the same cells are imaged and monitored in each imaging cycle. Such a requirement means that the positioning accuracy of the scanner holding the objective should be as high as possible, preferably on the scale of a few hundred nanometers. Such high precision in scanner motion is challenging and requires sophisticated engineering. But the demand is necessary to ensure the objective repeatedly revisits the same exact spot.

3. Acquisition speed

The term “time is money” takes on a whole new meaning when it comes to compound screens of tens of thousands of different chemicals and/or their combinations. Such massive screens often involve a comprehensive scan of the entire plate, followed by automated image analysis of all acquired images.

Higher scan speeds allow single labs to become more high-throughput and process more samples at any given time. This issue of throughput has an acute significance not only in large pharma companies that run large-scale drug screening campaigns but also in academic laboratories or core facilities that serve multiple projects or laboratories simultaneously. A higher scan speed means more users can access the system on any given day. Results can be obtained faster, whether they are intended for publication or study design.

High content imaging platforms designed with these considerations in mind can readily scan 96 locations (i.e., wells) in four fluorescent channels in less than 1 minute and 40 seconds, using 50ms camera exposure time per channel.  As such, systems can be benchmarked and compared at an early stage if their manufacturer states expected scan times for specified conditions.

4. Ease of use

High content imaging systems are a work of precision engineering, but their primary users are biologists. The interface of any HCI platform should not reflect the underlying design complexity. Rather, it should empower biologists to utilize the platform’s wide range of tools and capabilities as easily and efficiently as possible.

It is thusly important to pay attention to the user interface when selecting a new system. Prospective buyers should always evaluate how intuitive it is to operate the software both for acquisition and image analysis to get a sense of its general ease of use. Equipment demonstrations indicate the intuitiveness of a system with how quickly users become comfortable using the system on their own. This quality will help with onboarding new users and ensure that biologists can perform more experiments at a faster pace.

The most user-friendly systems are designed with a simple interface requiring just a few button presses on a touchscreen, offering quick navigation and manual visualizations of your sample. Additional options include an analog joystick for a familiar and smooth visual scanning experience prior to initiating automated imaging.

Training for imaging with such a system does not take longer than half a day for any level of user, from the junior laboratory worker to the senior professor, or the most experienced technician. Ideally, only one additional half-day should be needed to learn how to use accompanying automated image analysis software.

5. Value for money

When trying to assess the cost-effectiveness of a high content imaging system, you need to consider the cost of the system and its productivity. The best return on investment (ROI) is obtained from a platform whose price is reasonable and offers very high scanning speeds that double the throughput of parallel systems. Also, quick user training on systems with an easy and intuitive user interface also effectively increases the ROI because it saves on the training time and facilitates the passing of knowledge and know-how between colleagues – each user should become productive with the system in no time.

Interested in high content imaging products? Contact a member of the IDEA Bio team today to request a demo of any of our systems.

Yael Geva, B.Sc. Biotechnology Engineering

Head of Operations

Yael is part of IDEA Bio-Medical team since 2015 and has vast experience supporting sales and marketing of scientific lab equipment, automated microscopy and image analysis software platforms.