Noise Reduction Method for Quantifying Nanoparticle Light Scattering in Low Magnification Dark-Field Microscope Far-Field Images.
Nanoparticles have become a powerful tool for cell imaging and biomolecule, cell and protein interaction studies, but are difficult to rapidly and accurately measure in most assays. Dark-field microscope (DFM) image analysis approaches used to quantify nanoparticles require high-magnification near-field (HN) images that are labor intensive due to a requirement for manual image selection and focal adjustments needed when identifying and capturing new regions of interest. Low-magnification far-field (LF) DFM imagery is technically simpler to perform but cannot be used as an alternate to HN-DFM quantification, since it is highly sensitive to surface artifacts and debris that can easily mask nanoparticle signal. We now describe a new noise reduction approach that markedly reduces LF-DFM image artifacts to allow sensitive and accurate nanoparticle signal quantification from LF-DFM images. We have used this approach to develop a "Dark Scatter Master" (DSM) algorithm for the popular NIH image analysis program ImageJ, which can be readily adapted for use with automated high-throughput assay analyses. This method demonstrated robust performance quantifying nanoparticles in different assay formats, including a novel method that quantified extracellular vesicles in patient blood sample to detect pancreatic cancer cases. Based on these results, we believe our LF-DFM quantification method can markedly decrease the analysis time of most nanoparticle-based assays to impact both basic research and clinical analyses.
Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Avenue, Houston, TX 77030, United States.
Dali
D
Sun
Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Avenue, Houston, TX 77030, United States.
Jia
J
Fan
Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Avenue, Houston, TX 77030, United States.
Chang
C
Liu
Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Avenue, Houston, TX 77030, United States.
Yang
Y
Liu
Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Avenue, Houston, TX 77030, United States.
Yang
Y
Bu
Department of Nanomedicine, Houston Methodist Research Institute, 6670 Bertner Avenue, Houston, TX 77030, United States.
Christopher J
CJ
Lyon
School of Biological and Health Systems Engineering, Virginia G. Piper Biodesign Center for Personalized Diagnostics, The Biodesign Institute, Arizona State University, 727 E. Tyler St. B 130-B, Tempe, AZ 85287, United States.
Ye
Y
Hu
D000465:Algorithms; D055910:Antibodies, Immobilized / Q000737:chemistry / Q000378:metabolism; D016477:Artifacts; D001426:Bacterial Proteins / Q000378:metabolism; D006046:Gold / Q000737:chemistry; D006801:Humans; D007118:Immunoassay; D053768:Metal Nanoparticles / Q000737:chemistry*; D008853:Microscopy / Q000379:methods*; D013205:Staphylococcal Protein A / Q000378:metabolism
D055910:Antibodies, Immobilized; D001426:Bacterial Proteins; C034284:IgG Fc-binding protein, Streptococcus; D013205:Staphylococcal Protein A; D006046:Gold