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Toward rapid, high-sensitivity, volume-constrained biomarker quantification and validation using backscattering interferometry.

ABSTRACT: Realizing personalized medicine, which promises to enable early disease detection, efficient diagnostic staging, and therapeutic efficacy monitoring, hinges on biomarker quantification in patient samples. Yet, the lack of a sensitive technology and assay methodology to rapidly validate biomarker candidates continues to be a bottleneck for clinical translation. In our first direct and quantitative comparison of backscattering interferometry (BSI) to fluorescence sensing by ELISA, we show that BSI could aid in overcoming this limitation. The analytical validation study was performed against ELISA for two biomarkers for lung cancer detection: Cyfra 21-1 and Galectin-7. Spiked serum was used for calibration and comparison of analytical figures of merit, followed by analysis of blinded patient samples. Using the ELISA antibody as the probe chemistry in a mix-and-read assay, BSI provided significantly lower detection limits for spiked serum samples with each of the biomarkers. The limit of quantification (LOQ) for Cyrfa-21-1 was measured to be 230 pg/mL for BSI versus 4000 pg/mL for ELISA, and for Galectin-7, it was 13 pg/mL versus 500 pg/mL. The coefficient of variation for 5 day, triplicate determinations was <15% for BSI and <10% for ELISA. The two techniques correlated well, ranging from 3-29% difference for Cyfra 21-1 in a blinded patient sample analysis. The label-free and free-solution operation of BSI allowed for a significant improvement in analysis speed, with greater ease, improved LOQ values, and excellent day-to-day reproducibility. In this unoptimized format, BSI required 5.5-fold less sample quantity needed for ELISA (a 10 point calibration curve measured in triplicate required 36 μL of serum for BSI vs 200 μL for ELISA). The results indicate that the BSI platform can enable rapid, sensitive analytical validation of serum biomarkers and should significantly impact the validation bottleneck of biomarkers.

SUBMITTER: Olmsted IR

PROVIDER: S-EPMC4215853 | biostudies-other | 2014 Aug

REPOSITORIES: biostudies-other

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Project description:Background Three-dimensional (3D) fractional moving blood volume (FMBV) derived from 3D power Doppler US has been proposed for noninvasive approximation of perfusion. However, 3D FMBV has never been applied in animals against a ground truth. Purpose To determine the correlation between 3D FMBV and the reference standard of fluorescent microspheres (FMS) for measurement of renal perfusion in a porcine model. Materials and Methods From February 2017 to September 2017, adult pigs were administered FMS before and after measurement of renal 3D FMBV at baseline (100%) and approximately 75%, 50%, and 25% flow levels by using US machines from two different vendors. The 3D power Doppler US volumes were converted and segmented, and correlations between FMS and 3D FMBV were made with simple linear regression (r2). Similarity and reproducibility of manual segmentation were determined with the Dice similarity coefficient and 3D FMBV reproducibility (intraclass correlation coefficient [ICC]). Results Thirteen pigs were studied with 33 flow measurements. Kidney volume (mean Dice similarity coefficient ± standard deviation, 0.89 ± 0.01) and renal segmentation (coefficient of variation = 12.6%; ICC = 0.86) were consistent. The 3D FMBV calculations had high reproducibility (ICC = 0.97; 95% confidence interval: 0.96, 0.98). The 3D FMBV per-pig correlation showed excellent correlation for US machines from both vendors (mean r2 = 0.96 [range, 0.92-1.0] and 0.93 [range, 0.78-1.0], respectively). The correlation between 3D FMBV and perfusion measured with microspheres was high for both US machines (r2 = 0.80 [P < .001] and 0.70 [P < .001], respectively). Conclusion The strong correlation between three-dimensional (3D) fractional moving blood volume (FMBV) and fluorescent microspheres indicates that 3D FMBV shows excellent correlation to perfusion and good reproducibility. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Morrell et al in this issue.

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Toward rapid, high-sensitivity, volume-constrained biomarker quantification and validation using backscattering interferometry.

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