The junior researchers Dr. Daniel Geiger, Tobias Neckernuß and Jonas Pfeil from Ulm have developed an innovative method for non-contact real-time analysis of cells and other particles. The analysis involves low data rates and correspondingly little effort. This is what makes the method so attractive for medical applications.
Three junior researchers at the Institute of Experimental Physics at the University of Ulm have developed a clever method for the optical analysis of cells, and they have done so without major project funding or company participation. Daniel Geiger, Tobias Neckernuß and Jonas Pfeil did however receive support from the department in which they work that is headed up by Prof. Dr. sc. nat. Othmar Marti, and the Institute of Microelectronics at the University of Ulm. “The team has provided us with tremendous support for developing the hardware solutions,” says Neckernuß who carried out the developmental work as part of his doctoral thesis, as did his two colleagues.
The technology on which the method is based is called optical deformation cytometry. In principle, the method is not new at all and has in fact been used for analyses for many years. It works as follows: cells contained in an aqueous medium become deformed as a result of the special flow conditions in a microchannel. More specifically, the approximately spherical cell is stretched in a process that is typically recorded with a high-speed camera. This enables the biomechanical properties of the cells, but also other parameters such as size, shape and morphology, to be examined without touching the cell. Neckernuß knows why this so important in cancer diagnosis, to name but one example: “The structure of the cytoskeleton and the membrane rigidity of cancer cells differs from that of healthy cells. For example, metastatic pancreatic cancer cells are usually “softer” than a patient’s healthy cells. If this method is used for analysing the blood of cancer patients, it will be possible in the future to find out how many cells can be deformed in a tumour-specific way. This in turn allows conclusions to be drawn on the course of the disease or therapy.”
A key challenge of the process is the generation and processing of the image data. High-speed cameras are not only very expensive, but taking 100,000 images per second quickly leads to data volumes of several gigabits per second, and all these data need to be stored and analysed. This requires powerful and expensive hardware. “Our innovation is the ability to process data directly on the sensor. We work with very low data rates and already start transforming the images as they are taken. We have developed our own algorithm for the image transformation process,” says Neckernuß. The researchers from Ulm have also developed the algorithms that are used to acquire the physical parameters, i.e. size, shape and speed of the cell.
The sensor delivers images in truly poor resolution: 30 by 30 pixels - that's 900 pixels per image. According to Neckernuß, however, this is more than sufficient, because the new process only depends on the difference between two images. "We have reduced the data rate by a factor of 1000 compared to the traditional method. The data is transferred directly to a so-called FPGA immediately after recording. FPGAs are small microcontrollers which are standard components of microelectronic devices." The whole process happens so fast that the researchers can provide a real-time analysis.
Based on a functional prototype in the form of a microchip with sensor, the team wants to turn the new process into concrete applications. The focus is initially on scientific issues. "The procedure is generally suitable for cell counting and sorting. There is no need to attach a fluorescent label to the cell. This means that we can work directly with the cells and still have the temporal solution that is needed to detect a cell. “In principle there is no reason not to use this type of real-time analysis as control in operating theatres during surgical interventions. It is equally conceivable to use the small and robust system for point-of-care diagnostics applications directly at the bedside.
However, the method is not only suitable for analysing cells, but also for particles in general in aqueous and even gaseous media. “Of course, it takes a certain engineering effort to convert the system from the fluid channel into the air channel. But fundamentally intervening with the technology is not necessary,” says Neckernuß referring to the feasibility of the system. In the long term, the team is specifically interested in finding ways to detect particle contaminations in cleanrooms. The team has already successfully tested the analysis of oil droplets in water. "We can analyse and sort a large number of droplets in a short time and with great accuracy. This makes the system suitable for test set-ups in the pharmaceutical industry,” says Neckernuß.
Overall particle size is very variable. “The method is not suitable for investigating nanoparticles, but anything is possible in the range of one to several hundred microns,” says Neckernuß. The authors also want to open up a dialogue with interested parties to adapt their technology to specific practical requirements. The range of opportunities is so great and promising that they have now decided to establish a company. "We are currently working on funding applications, are looking for investors and, at the same time, developing the technology further to market readiness," says Neckernuß.