Supramolecular Organization Predicts Protein Nanoparticle Delivery to Neutrophils for Acute Lung Inflammation Diagnosis and Treatment

Jacob W. Myerson; Priyal N. Patel; Nahal Habibi; Landis R. Walsh; Yi-Wei Lee; David C. Luther; Laura T. Ferguson; Michael H. Zaleski; Marco E. Zamora; Oscar A. Marcos-Contreras; Patrick M. Glassman; Ian Johnston; Elizabeth D. Hood; Tea Shuvaeva; Jason V. Gregory; Raisa Y. Kiseleva; Jia Nong; Kathryn M. Rubey; Colin F. Greineder; Samir Mitragotri; George S. Worthen; Vincent M. Rotello; Joerg Lahann; Vladimir R. Muzykantov; Jacob S. Brenner

SPECT/CT Imaging . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.04.15.037564 doi: bioRxiv preprint As described previously, 47 thirty minutes after injection of 80 µCi of 111 In-labeled nanogels, anesthetized mice were sacrificed by cervical dislocation. Mice were placed into a MiLabs U-SPECT (Utrecht, Netherlands) scanner bed. A region covering the entire body was scanned for 90 min using listmode acquisition. The animal was then moved, while maintaining position, to a MiLabs U-CT (Utrecht, Netherlands) for a fullbody CT scan using default acquisition parameters (240 µA, 50 kVp, 75 ms exposure, 0.75° step with 480 projections). For naïve mice and mice imaged after cardiogenic pulmonary edema, CT data was acquired as above without SPECT data. The SPECT data was reconstructed using reconstruction software provided by the manufacturer, with 400 µm voxels. The CT data were reconstructed using reconstruction software provided by the manufacturer, with 100 µm voxels. SPECT and CT data, in NIFTI format, were opened with ImageJ software (FIJI package). Background signal was removed from SPECT images by thresholding limits determined by applying Renyi entropic filtering, as implemented in ImageJ, to a SPECT image slice containing NGassociated 111 In in the liver. Background-subtracted pseudo-color SPECT images were overlayed on CT images and axial slices depicting lungs were selected for display, with CT thresholding set to emphasize negative contrast in the airspace of the lungs. ImageJ's built-in 3D modeling plugin was used to co-register background-subtracted pseudo-color SPECT images with CT images in three-dimensional reconstructions. CT image thresholding was set in the 3D modeling tool to depict skeletal structure alongside SPECT signal. For three-dimensional reconstructions of lung CT images, thresholding was set, as above, for contrast emphasizing the airspace of the lungs, with thresholding values standardized between different CT images (i.e. identical values were used for naïve and edematous lungs). Images were cropped in a cylinder to exclude the airspace outside of the animal, then contrast was inverted, allowing airspace to register bright CT signal and denser tissue to register as dark background. Three-dimensional reconstructions of the lung CT data, and co-registrations of SPECT data with lung CT data, were generated as above with ImageJ's 3D plugin applied to CT data cropped and partitioned for lung contrast. Quantification of CT attenuation employed ImageJ's measurement tool iteratively over axial slices, with measurement fields of view manually set to contain lungs and exclude surrounding tissue.