Lateral flow tests, also known as lateral flow immunochromatographic assays or rapid tests, are devices intended to detect the presence of a substance in a liquid sample without the need of specialized equipment. A lateral flow test is easy to read, and you do not need a specialized training. However, how it is possible to quantify a test like this one? With a lateral flow strip reader.
Whereas the human eye can semi-quantify according to the perceived intensity of the test line (response), a score card is needed to compare the result with a reference and be able to determine if it is a high positive, or a weak positive result. Furthermore, the result will always be subjective since depends on the operator’s visual acuity and environmental lighting conditions. With a lateral flow strip reader, we can objectively semi-quantify and even fully quantify using a calibration curve.
Thanks to the semi-quantification method, it is possible to stablish different thresholds to reflect a high or weak positive result. The lowest threshold value is the minimum value of the response to classify the test line as present; then the upper threshold, if exceeded, assigns a high positive result, and if not exceeded, a low positive result
How the lateral flow strip reader quantifies?
The lateral flow strip reader quantifies the test line response in terms of the analyte concentration of the sample. To achieve this, the reader uses calibration curves created previously with several replicates of standard samples with known concentrations. The calibration curve fits the dynamics of the sample and the analytical range so the reader is ready to interpret qualitative, semi-quantitative, or fully quantitative results.
The lateral flow strip reader converts the raw response (test line intensity) to a quantity response (i.e., concentration) through the calibration curve. Some of the quantity methods normalize the response (test line/control line) before applying the algorithm. Each reader deals with different algorithms. The most applied quantity method is the 4-PL method (4 – parameter logistic model), but there is also the step function, quadratic method, and linear method.
IUL’s iPeak, a colorimetric lateral flow reader
IUL’s iPeak® is a colorimetric rapid test reader that enhances the colors of your test. iPeak® is equipped with the Flash Eye technology that makes each iPeak® reproducible and repetitive. You can export and print the results, send them in real-time and integrate them to your laboratory information system (LIS) or send them to your server with one click.
The foundation of the Flash Eye technology is on the principles of machine vision illumination based on the Cloudy Day Lighting Illumination. iPeak® brings a camera that captures the image of the test illuminated from LED lights situated in the most studied geometry which allows a precise and uniform illumination.
This technology avoids reflections and shadows, diffusing and homogenizing the light in a chamber, which converts the iPeak® the best rapid test reader. An in-house algorithm processes the image, inspired on procedures used in radar technologies able to detect very weak signals embedded in a noisy background and increase the reliability of the results.
In other words, the science behind the iPeak® is what makes iPeak® unique and sophisticated. Its leverage point is to achieve the maximum sensitivity, to detect and even quantify the lines of a lateral flow assay. iPeak® is the result when mathematics and physics join and convert the iPeak®’s core into the ultimate lateral flow reader.
Quantifier methods of iPeak
Currently iPeak® can deal with 4 different quantifier methods apart from the qualitative method; all of them can be chosen to prior normalize or not to normalize the test line response to the control line response:
- 5PL, 4PL: Four parameter logistic curve is a regression model that follows a sigmoidal or “s” shape. Many bioassays are behaving this way since only are lineal in a specific part of the curve.
- Step function: step function needs five parameters. Returns one of the 3 user-selected textual results depending on which thresholds P2, P4 have been exceeded by the response.
- Quadratic: Second-order polynomial.
- Linear: First-order polynomial.