Improved detectability and signal strength for rotating phase fluorescence immunoassays through image processing

Abstract

Fluorescence immunoassays based on rotating solid phase have shown promise of lowered detection limits, among other advantages. However, intrinsic background distortion effects have limited their utility. Here, novel image processing strategies are used to minimize these effects and improve the estimate of concentration and lower the detection limit. This initial demonstration of a new processing capability is performed on data for a protein, myoglobin, which is a biomarker for acute myocardial infarction. For these data, compared with published results, the detection limit is improved by a factor of approximately one hundred (to 700 fM), which is competitive with or better than other immunoassay strategies (ELISA, for example) that are fully developed. This work suggests that image and video processing technologies can provide a valuable alternative approach to biochemical detection and concentration estimation.

Homogeneous Biosensing Based on Magnetic Particle Labels

“…Here, however, the only assay that was performed strictly without any washing step was the competitive format type assay in buffer, while all other experiments included at least one washing step [ 221 ]. This is also true for the most recent study by the group, where following further refinement of their image analysis procedure [ 222 ], they demonstrate highly sensitive detection of three cardiac biomarkers (detection limits: myoglobin ~360 aM, heart-type fatty acid binding protein (H-FABP) ~67 fM, troponin I ~42 fM) [ 223 ]. The biomarkers are spiked into buffer solutions and are detected by a sandwich immunoassay format performed on magnetically rotated particle clusters [ 223 ].…”

Sensitive detection of cardiac biomarkers using a magnetic microbead immunoassay

“…The overall noise power is reduced while signal power is increased. 41 This, coupled to the increase in S/N through optimal data acquisition conditions, allowed for a five-fold improvement in assay sensitivity.…”

“…Although the lowest concentrations detected could not be quantified due to high variations in signal, the potential exists to improve quantitative sensitivity through coupling to available signal processing approaches. 41 Using this approach, the detection limit of previously published data has been improved by a factor of 100. If the same factor of improvement and reduction in uncertainty for a given sample was realized for the data collected in this work, quantitation of the lowest sample data collected would be possible.…”

“…Signal processing strategies offer the potential to improve detection limits through the identification of specific signal generating surfaces and reduction of background elements to reduce the variation observed in signal intensity for low concentration samples. 41 Surface localization is of use in image processing because it creates distinct signal objects that are easier to detect and quantify compared to signal spread over the entire field of view. Creating these distinct signal objects allows for segmentation of collected images and the quantitation of fluorescent species bound in the immunoassay without the influence of diffuse background fluorescence.…”

“…Additionally, while signal clusters contributed to less than 30% of the region selected, the average pixel intensity was calculated for the entire selected area, including both signal and noise. 41 Signal processing studies performed on this data conclude that by calculating pixel intensity for the entire image selection, and by only two of the signal clusters contributing to target quantication, a large portion of the signal power is lost while the noise power is increased. 41 By manually segmenting data and selecting all rotors in each frame (492 Â 396 pixels) as was done in this work, both issues observed with previous analysis methods are solved.…”