Daniel Eugene Meyer

Estimating amounts of iron oxide from gradient echo images

Rat legs directly injected with superparamagnetic iron oxide (SPIO) were studied by dual‐echo, gradient‐echo imaging. The amount of iron injected was estimated using a point dipole model for the SPIO injection site. Saturation magnetization of 6:1 PEG/amino modified silane‐coated iron oxide particles with 5‐ to 6‐nm core and 20–25 hydrodynamic diameter was ∼110 emu/g of iron. Estimates of the amount of iron injected made from signal void volumes surrounding SPIO centers yielded erroneous results varying with sample orientation in the scanner and echo time (TE). For example, a 10 μL, 3‐μg iron injection produced signal void volumes of 80 and 210 μL at TE of 9.8 and 25 ms, respectively, giving apparent iron contents of 6 ± 1 and 10 ± 2 μg respectively. A more effective approach uses the phase difference between two gradient recalled echo images. To estimate iron content, this approach fits the expected (3 cos2θ − 1)/|r|3 spatial phase distribution to the observed phase differences. Extraneous phase effects made fitting phase at a single TE ineffective. With the dual echo method, 18 independent estimates were 2.48 ± 0.26 μg std, independently of sample orientation. Estimates in empty control regions were −90 and −140 ng. A 1‐μg injection indicated 0.5, 1.2, and 1.2 μg. Magn Reson Med, 2009.

Evaluation of the novel USPIO GEH121333 for MR imaging of cancer immune responses.

Tumor-associated macrophages (TAM) maintain a chronic inflammation in cancers, which is associated with tumor aggressiveness and poor prognosis. The purpose of this study was to: (1) evaluate the pharmacokinetics and tolerability of the novel ultrasmall superparamagnetic iron oxide nanoparticle (USPIO) compound GEH121333; (2) assess whether GEH121333 can serve as a MR imaging biomarker for TAM; and (3) compare tumor MR enhancement profiles between GEH121333 and ferumoxytol. Blood half-lives of GEH121333 and ferumoxytol were measured by relaxometry (n = 4 each). Tolerance was assessed in healthy rats injected with high dose GEH121333, vehicle or saline (n = 4 each). Animals were monitored for 7 days regarding body weight, complete blood counts and serum chemistry, followed by histological evaluation of visceral organs. MR imaging was performed on mice harboring MMTV-PyMT-derived breast adenocarcinomas using a 7 T scanner before and up to 72 h post-injection (p.i.) of GEH121333 (n = 10) or ferumoxytol (n = 9). Tumor R1, R2* relaxation rates were compared between different experimental groups and time points, using a linear mixed effects model with a random effect for each animal. MR data were correlated with histopathology. GEH121333 showed a longer circulation half-life than ferumoxytol. Intravenous GEH121333 did not produce significant adverse effects in rats. All tumors demonstrated significant enhancement on T1, T2 and T2*-weighted images at 1, 24, 48 and 72 h p.i. GEH121333 generated stronger tumor T2* enhancement than ferumoxytol. Histological analysis verified intracellular compartmentalization of GEH121333 by TAM at 24, 48 and 72 h p.i. MR imaging with GEH121333 nanoparticles represents a novel biomarker for TAM assessment. This new USPIO MR contrast agent provides a longer blood half-life and better TAM enhancement compared with the iron supplement ferumoxytol. Copyright

Performance of Redox Active and Chelatable Iron Assays to Determine Labile Iron Release From Intravenous Iron Formulations

Emerging data from global markets outside the United States, where many generic iron sucrose formulations are available, have revealed that non‐US generic intravenous (i.v.) iron formulations may have iron release profiles that differ from the reference listed drug (RLD). The first generic i.v. iron approved in the United States was sodium ferric gluconate complex in 2011. We evaluated chelatable and redox labile iron assay methods to measure the amount of labile iron released from i.v. iron formulations in biorelevant matrices in vitro. The majority of published labile iron assays evaluated were not suitable for use in vitro due to overwhelming interference by the presence of the i.v. iron products. However, an optimized high‐performance liquid chromatography (HPLC)‐based method performed well for use in vitro labile iron detection in a biorelevant matrix. Application of this method may enhance bioequivalence evaluation of generic i.v. iron formulations in the future.

Pointwise mutual information quantifies intratumor heterogeneity in tissue sections labeled with multiple fluorescent biomarkers

Background: Measures of spatial intratumor heterogeneity are potentially important diagnostic biomarkers for cancer progression, proliferation, and response to therapy. Spatial relationships among cells including cancer and stromal cells in the tumor microenvironment (TME) are key contributors to heterogeneity. Methods: We demonstrate how to quantify spatial heterogeneity from immunofluorescence pathology samples, using a set of 3 basic breast cancer biomarkers as a test case. We learn a set of dominant biomarker intensity patterns and map the spatial distribution of the biomarker patterns with a network. We then describe the pairwise association statistics for each pattern within the network using pointwise mutual information (PMI) and visually represent heterogeneity with a two-dimensional map. Results: We found a salient set of 8 biomarker patterns to describe cellular phenotypes from a tissue microarray cohort containing 4 different breast cancer subtypes. After computing PMI for each pair of biomarker patterns in each patient and tumor replicate, we visualize the interactions that contribute to the resulting association statistics. Then, we demonstrate the potential for using PMI as a diagnostic biomarker, by comparing PMI maps and heterogeneity scores from patients across the 4 different cancer subtypes. Estrogen receptor positive invasive lobular carcinoma patient, AL13-6, exhibited the highest heterogeneity score among those tested, while estrogen receptor negative invasive ductal carcinoma patient, AL13-14, exhibited the lowest heterogeneity score. Conclusions: This paper presents an approach for describing intratumor heterogeneity, in a quantitative fashion (via PMI), which departs from the purely qualitative approaches currently used in the clinic. PMI is generalizable to highly multiplexed/hyperplexed immunofluorescence images, as well as spatial data from complementary in situ methods including FISSEQ and CyTOF, sampling many different components within the TME. We hypothesize that PMI will uncover key spatial interactions in the TME that contribute to disease proliferation and progression.

In vitro and in vivo DFO-chelatable labile iron release profiles among commercially available intravenous iron nanoparticle formulations

ABSTRACT Intravenous (IV) iron formulations are complex colloidal suspensions of iron oxide nanoparticles. Small changes in formulation can allow more labile iron to be released after injection causing toxicity. Thus, bioequivalence (BE) evaluation of generic IV iron formulations remains challenging. We evaluated labile iron release in vitro and in vivo using a high performance liquid chromatography chelatable iron assay to develop a relational model to support BE. In vitro labile iron release and in vivo labile iron pharmacokinetics were evaluated for Venofer®, Ferrlecit®, generic sodium ferric gluconate complex, InFeD®, Feraheme® and a pre‐clinical formulation GE121333. Labile iron release profiles were studied in vitro in 150mM saline and a biorelevant matrix (rat serum) at 0.952 mgFe/mL. In vivo plasma labile iron concentration‐time profiles (t0–240min) were studied in rats after a 40 mgFe/kg IV dose. In vitro labile iron release in saline was significantly higher compared to rat serum, especially with InFeD®. An in vitro release constant (iKr) was calculated which correlated well with maximal plasma concentrations in the in vivo rat PK model (R2=0.711). These data suggest an in vitro to in vivo correlation model of labile iron release kinetics could be applied to BE. Other generic IV iron formulations need to be studied to validate this model. HIGHLIGHTSIntravenous iron formulations are complex drugs that are colloidal suspensions of iron oxide nanoparticles.Small formulation changes that are not discerned by physicochemical characterization may allow for more labile iron release.These characteristics of IV iron formulations make bioequivalence evaluation challenging.An in vitro to in vivo correlation model for labile iron release could improve bioequivalence evaluation.

Multiparametric characterization of response to anti-angiogenic therapy using USPIO contrast-enhanced MRI in combination with dynamic contrast-enhanced MRI: SSC- & DCE-MRI of Bevacizumab Response

Steady state susceptibility contrast (SSC)‐MRI provides information on vascular morphology but is a rarely used method.

Immunization Elicits Antigen-Specific Antibody Sequestration in Dorsal Root Ganglia Sensory Neurons

The immune and nervous systems are two major organ systems responsible for host defense and memory. Both systems achieve memory and learning that can be retained, retrieved, and utilized for decades. Here, we report the surprising discovery that peripheral sensory neurons of the dorsal root ganglia (DRGs) of immunized mice contain antigen-specific antibodies. Using a combination of rigorous molecular genetic analyses, transgenic mice, and adoptive transfer experiments, we demonstrate that DRGs do not synthesize these antigen-specific antibodies, but rather sequester primarily IgG1 subtype antibodies. As revealed by RNA-seq and targeted quantitative PCR (qPCR), dorsal root ganglion (DRG) sensory neurons harvested from either naïve or immunized mice lack enzymes (i.e., RAG1, RAG2, AID, or UNG) required for generating antibody diversity and, therefore, cannot make antibodies. Additionally, transgenic mice that express a reporter fluorescent protein under the control of Igγ1 constant region fail to express Ighg1 transcripts in DRG sensory neurons. Furthermore, neural sequestration of antibodies occurs in mice rendered deficient in neuronal Rag2, but antibody sequestration is not observed in DRG sensory neurons isolated from mice that lack mature B cells [e.g., Rag1 knock out (KO) or μMT mice]. Finally, adoptive transfer of Rag1-deficient bone marrow (BM) into wild-type (WT) mice or WT BM into Rag1 KO mice revealed that antibody sequestration was observed in DRG sensory neurons of chimeric mice with WT BM but not with Rag1-deficient BM. Together, these results indicate that DRG sensory neurons sequester and retain antigen-specific antibodies released by antibody-secreting plasma cells. Coupling this work with previous studies implicating DRG sensory neurons in regulating antigen trafficking during immunization raises the interesting possibility that the nervous system collaborates with the immune system to regulate antigen-mediated responses.

Blood vessel characterization using virtual 3D models and convolutional neural networks in fluorescence microscopy

We report an automated method for characterization of microvessel morphology in micrographs of brain tissue sections to enable the facile, quantitative analysis of vascular differences across large datasets consisting of hundreds of images with thousands of blood vessel objects. Our objective is to show that virtual 3D parametric models of vasculature are adequately capable of representing the morphology of naturally acquired data in neuropathology. In this work, we focus on three distinct morphologies that are most frequently observed in formalin-fixed, paraffin-embedded (FFPE) human brain tissue samples: single blood vessels showing no (or collapsed) significant lumen (“RoundLumen-”); single blood vessels with distinct lumen (“RoundLumen+”); two blood vessels bundled together in close proximity (“Twins”). The analysis involves extraction of features using pre-trained convolutional neural networks. A hierarchical classification is performed to distinguish single blood vessels (RoundLumen) from Twins; followed by a more granular classification between RoundLumen- and RoundLumen+. A side-by-side comparison of the virtual and natural data models is presented. We observed that classification models built on the virtual data perform well achieving accuracies of 92.8% and 98.3% for the two aforementioned classification tasks respectively.