Improved threshold selection for the determination of volume of distribution of nanoparticles administered by convection-enhanced delivery

Nanotechnology, in conjunction with convection-enhanced delivery (CED), has gained traction as a promising method to treat many debilitating neurological diseases, including gliomas. One of the key parameters to evaluate the effectiveness of delivery is the volume of distribution (V_d) of nanoparticles within the brain parenchyma. Measurements of V_d are commonly made using fluorescent reporter systems. However, reported analyses lack accurate and robust methods for determining V_d. Current methods face the problems of varying background intensities between images, high intensity aggregates that can shift intensity distributions, and faint residual backgrounds that can occur as artifacts of fluorescent imaging. These problems can cause inaccurate results to be reported when a percentage of the maximum intensity is set as the threshold value. Here we show an implementation of Otsu's method more reliably selects accurate threshold values than the fixed-threshold method. We also introduce a goodness of fit value η that quantifies the appropriateness of using Otsu's method to calculate V_d. Adoption of Otsu's method and reporting of η may help standardize fluorescent image analysis of nanoparticles administered by convection-enhanced delivery.