Evaluating the immunologically "cold" tumor microenvironment after treatment with immune checkpoint inhibitors utilizing PET imaging of CD4 + and CD8 + T cells in breast cancer mouse models.

BACKGROUND: Immune-positron emission tomography (PET) imaging with tracers that target CD8 and granzyme B has shown promise in predicting the therapeutic response following immune checkpoint blockade (ICB) in immunologically "hot" tumors. However, immune dynamics in the low T-cell infiltrating "cold" tumor immune microenvironment during ICB remain poorly understood. This study uses molecular imaging to evaluate changes in CD4 + T cells and CD8 + T cells during ICB in breast cancer models and examines biomarkers of response. METHODS: [89Zr]Zr-DFO-CD4 and [89Zr]Zr-DFO-CD8 radiotracers were used to quantify changes in intratumoral and splenic CD4 T cells and CD8 T cells in response to ICB treatment in 4T1 and MMTV-HER2 mouse models, which represent immunologically "cold" tumors. A correlation between PET quantification metrics and long-term anti-tumor response was observed. Further biological validation was obtained by autoradiography and immunofluorescence. RESULTS: Following ICB treatment, an increase in the CD8-specific PET signal was observed within 6 days, and an increase in the CD4-specific PET signal was observed within 2 days in tumors that eventually responded to immunotherapy, while no significant differences in CD4 or CD8 were found at the baseline of treatment that differentiated responders from nonresponders. Furthermore, mice whose tumors responded to ICB had a lower CD8 PET signal in the spleen and a higher CD4 PET signal in the spleen compared to non-responders. Intratumoral spatial heterogeneity of the CD8 and CD4-specific PET signals was lower in responders compared to non-responders. Finally, PET imaging, autoradiography, and immunofluorescence signals were correlated when comparing in vivo imaging to ex vivo validations. CONCLUSIONS: CD4- and CD8-specific immuno-PET imaging can be used to characterize the in vivo distribution of CD4 + and CD8 + T cells in response to immune checkpoint blockade. Imaging metrics that describe the overall levels and distribution of CD8 + T cells and CD4 + T cells can provide insight into immunological alterations, predict biomarkers of response to immunotherapy, and guide clinical decision-making in those tumors where the kinetics of the response differ.

RORγt-Expressing Pathogenic CD4+ T Cells Cause Brain Inflammation during Chronic Colitis.

Neurobehavioral disorders and brain abnormalities have been extensively reported in both Crohn's disease and ulcerative colitis patients. However, the mechanism causing neuropathological disorders in inflammatory bowel disease patients remains unknown. Studies have linked the Th17 subset of CD4+ T cells to brain diseases associated with neuroinflammation and cognitive impairment, including multiple sclerosis, ischemic brain injury, and Alzheimer's disease. To better understand how CD4+ T lymphocytes contribute to brain pathology in chronic intestinal inflammation, we investigated the development of brain inflammation in the T cell transfer model of chronic colitis. Our findings demonstrate that CD4+ T cells infiltrate the brain of colitic Rag1 -/- mice in proportional levels to colitis severity. Colitic mice developed hypothalamic astrogliosis that correlated with neurobehavioral disorders. Moreover, the brain-infiltrating CD4+ T cells expressed Th17 cell transcription factor retinoic acid-related orphan receptor γt (RORγt) and displayed a pathogenic Th17 cellular phenotype similar to colonic Th17 cells. Adoptive transfer of RORγt-deficient naive CD4+ T cells failed to cause brain inflammation and neurobehavioral disorders in Rag1 -/- recipients, with significantly less brain infiltration of CD4+ T cells. The finding is mirrored in chronic dextran sulfate sodium-induced colitis in Rorcfl/fl Cd4-Cre mice that showed lower frequency of brain-infiltrating CD4+ T cells and astrogliosis despite onset of significantly more severe colitis compared with wild-type mice. These findings suggest that pathogenic RORγt+CD4+ T cells that aggravate colitis migrate preferentially into the brain, contributing to brain inflammation and neurobehavioral disorders, thereby linking colitis severity to neuroinflammation.

Analysis of simplicial complexes to determine when to sample for quantitative DCE MRI of the breast.

PURPOSE: A method is presented to select the optimal time points at which to measure DCE-MRI signal intensities, leaving time in the MR exam for high-spatial resolution image acquisition. THEORY: Simplicial complexes are generated from the Kety-Tofts model pharmacokinetic parameters Ktrans and ve . A geometric search selects optimal time points for accurate estimation of perfusion parameters. METHODS: The DCE-MRI data acquired in women with invasive breast cancer (N = 27) were used to retrospectively compare parameter maps fit to full and subsampled time courses. Simplicial complexes were generated for a fixed range of Kety-Tofts model parameters and for the parameter ranges weighted by estimates from the fully sampled data. The largest-area manifolds determined the optimal three time points for each case. Simulations were performed along with retrospectively subsampled data fits. The agreement was computed between the model parameters fit to three points and those fit to all points. RESULTS: The optimal three-point sample times were from the data-informed simplicial complex analysis and determined to be 65, 204, and 393 s after arrival of the contrast agent to breast tissue. In the patient data, tumor-median parameter values fit using all points and the three selected time points agreed with concordance correlation coefficients of 0.97 for Ktrans and 0.67 for ve . CONCLUSION: It is possible to accurately estimate pharmacokinetic parameters from three properly selected time points inserted into a clinical DCE-MRI breast exam. This technique can provide guidance on when to capture images for quantitative data between high-spatial-resolution DCE-MRI images.

Evaluation of a CD206-Targeted Peptide for PET Imaging of Macrophages in Syngeneic Mouse Models of Cancer.

Tumor-associated macrophages (TAMs) are large phagocytic cells that play numerous roles in cancer biology and are an important component of the relationship between immune system response and tumor progression. The peptide, RP832c, targets the Mannose Receptor (CD206) expressed on M2-like macrophages and is cross-reactive to both human and murine CD206. Additionally, it exhibits therapeutic properties through its ability to shift the population of TAMs from an M2-like (protumor) toward an M1-like phenotype (antitumor) and has demonstrated promise in inhibiting tumor resistance in PD-L1 unresponsive melanoma murine models. In addition, it has shown inhibition in bleomycin-induced pulmonary fibrosis through interactions with CD206 macrophages.1,2 Our work aims to develop a novel CD206 positron emission tomography (PET) imaging probe based on RP832c (Kd = 5.64 µM) as a direct, noninvasive method for the assessment of TAMs in mouse models of cancer. We adapted RP832c to incorporate the chelator DOTA to allow for radiolabeling with the PET isotope 68Ga (t1/2 = 68 min; ß+ = 89%). In vitro stability studies were conducted in mouse serum up to 3 h. The in vitro binding characteristics of [68Ga]RP832c to CD206 were determined by a protein plate binding assay and Surface Plasmon Resonance (SPR). PET imaging and biodistribution studies were conducted in syngeneic tumor models. Stability studies in mouse serum demonstrated that 68Ga remained complexed up to 3 h (less than 1% free 68Ga). Binding affinity studies demonstrated high binding of [68Ga]RP832c to mouse CD206 protein and that the binding of the tracer was able to be blocked significantly when incubated with a blocking solution of native RP832c. PET imaging and biodistribution studies in syngeneic tumor models demonstrated uptake in tumor and CD206 expressing organs of [68Ga]RP832c. A significant correlation was found between the percentage of CD206 present in each tumor imaged with [68Ga]RP832c and PET imaging mean standardized uptake values in a CT26 mouse model of cancer. The data shows that [68Ga]RP832c represents a promising candidate for macrophage imaging in cancer and other diseases.

Mathematical Model of Triple-Negative Breast Cancer in Response to Combination Chemotherapies.

Triple-negative breast cancer (TNBC) is a heterogenous disease that is defined by its lack of targetable receptors, thus limiting treatment options and resulting in higher rates of metastasis and recurrence. Combination chemotherapy treatments, which inhibit tumor cell proliferation and regeneration, are a major component of standard-of-care treatment of TNBC. In this manuscript, we build a coupled ordinary differential equation model of TNBC with compartments that represent tumor proliferation, necrosis, apoptosis, and immune response to computationally describe the biological tumor affect to a combination of chemotherapies, doxorubicin (DRB) and paclitaxel (PTX). This model is parameterized using longitudinal [18F]-fluorothymidine positron emission tomography (FLT-PET) imaging data which allows for a noninvasive molecular imaging approach to quantify the tumor proliferation and tumor volume measurements for two murine models of TNBC. Animal models include a human cell line xenograft model, MDA-MB-231, and a syngeneic 4T1 mammary carcinoma model. The mathematical models are parameterized and the percent necrosis at the end time point is predicted and validated using histological hematoxylin and eosin (H&E) data. Global Sobol' sensitivity analysis is conducted to further understand the role each parameter plays in the model's goodness of fit to the data. In both the MDA-MB-231 and the 4T1 tumor models, the designed mathematical model can accurately describe both tumor volume changes and final necrosis volume. This can give insight into the ordering, dosing, and timing of DRB and PTX treatment. More importantly, this model can also give insight into future novel combinations of therapies and how the immune system plays a role in therapeutic response to TNBC, due to its calibration to two types of TNBC murine models.

Optimizing combination therapy in a murine model of HER2+ breast cancer.

Human epidermal growth factor receptor 2 positive (HER2+) breast cancer is frequently treated with drugs that target the HER2 receptor, such as trastuzumab, in combination with chemotherapy, such as doxorubicin. However, an open problem in treatment design is to determine the therapeutic regimen that optimally combines these two treatments to yield optimal tumor control. Working with data quantifying temporal changes in tumor volume due to different trastuzumab and doxorubicin treatment protocols in a murine model of human HER2+ breast cancer, we propose a complete framework for model development, calibration, selection, and treatment optimization to find the optimal treatment protocol. Through different assumptions for the drug-tumor interactions, we propose ten different models to characterize the dynamic relationship between tumor volume and drug availability, as well as the drug-drug interaction. Using a Bayesian framework, each of these models are calibrated to the dataset and the model with the highest Bayesian information criterion weight is selected to represent the biological system. The selected model captures the inhibition of trastuzumab due to pre-treatment with doxorubicin, as well as the increase in doxorubicin efficacy due to pre-treatment with trastuzumab. We then apply optimal control theory (OCT) to this model to identify two optimal treatment protocols. In the first optimized protocol, we fix the maximum dosage for doxorubicin and trastuzumab to be the same as the maximum dose delivered experimentally, while trying to minimize tumor burden. Within this constraint, optimal control theory indicates the optimal regimen is to first deliver two doses of trastuzumab on days 35 and 36, followed by two doses of doxorubicin on days 37 and 38. This protocol predicts an additional 45% reduction in tumor burden compared to that achieved with the experimentally delivered regimen. In the second optimized protocol we fix the tumor control to be the same as that obtained experimentally, and attempt to reduce the doxorubicin dose. Within this constraint, the optimal regimen is the same as the first optimized protocol but uses only 43% of the doxorubicin dose used experimentally. This protocol predicts tumor control equivalent to that achieved experimentally. These results strongly suggest the utility of mathematical modeling and optimal control theory for identifying therapeutic regimens maximizing efficacy and minimizing toxicity.

Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting.

BACKGROUND: The purpose of this study was to determine whether advanced quantitative magnetic resonance imaging (MRI) can be deployed outside of large, research-oriented academic hospitals and into community care settings to predict eventual pathological complete response (pCR) to neoadjuvant therapy (NAT) in patients with locally advanced breast cancer. METHODS: Patients with stage II/III breast cancer (N = 28) were enrolled in a multicenter study performed in community radiology settings. Dynamic contrast-enhanced (DCE) and diffusion-weighted (DW)-MRI data were acquired at four time points during the course of NAT. Estimates of the vascular perfusion and permeability, as assessed by the volume transfer rate (Ktrans) using the Patlak model, were generated from the DCE-MRI data while estimates of cell density, as assessed by the apparent diffusion coefficient (ADC), were calculated from DW-MRI data. Tumor volume was calculated using semi-automatic segmentation and combined with Ktrans and ADC to yield bulk tumor blood flow and cellularity, respectively. The percent change in quantitative parameters at each MRI scan was calculated and compared to pathological response at the time of surgery. The predictive accuracy of each MRI parameter at different time points was quantified using receiver operating characteristic curves. RESULTS: Tumor size and quantitative MRI parameters were similar at baseline between groups that achieved pCR (n = 8) and those that did not (n = 20). Patients achieving a pCR had a larger decline in volume and cellularity than those who did not achieve pCR after one cycle of NAT (p < 0.05). At the third and fourth MRI, changes in tumor volume, Ktrans, ADC, cellularity, and bulk tumor flow from baseline (pre-treatment) were all significantly greater (p < 0.05) in the cohort who achieved pCR compared to those patients with non-pCR. CONCLUSIONS: Quantitative analysis of DCE-MRI and DW-MRI can be implemented in the community care setting to accurately predict the response of breast cancer to NAT. Dissemination of quantitative MRI into the community setting allows for the incorporation of these parameters into the standard of care and increases the number of clinical community sites able to participate in novel drug trials that require quantitative MRI.

[89Zr]-Pertuzumab PET Imaging Reveals Paclitaxel Treatment Efficacy Is Positively Correlated with HER2 Expression in Human Breast Cancer Xenograft Mouse Models.

Paclitaxel (PTX) treatment efficacy varies in breast cancer, yet the underlying mechanism for variable response remains unclear. This study evaluates whether human epidermal growth factor receptor 2 (HER2) expression level utilizing advanced molecular positron emission tomography (PET) imaging is correlated with PTX treatment efficacy in preclinical mouse models of HER2+ breast cancer. HER2 positive (BT474, MDA-MB-361), or HER2 negative (MDA-MB-231) breast cancer cells were subcutaneously injected into athymic nude mice and PTX (15 mg/kg) was administrated. In vivo HER2 expression was quantified through [89Zr]-pertuzumab PET/CT imaging. PTX treatment response was quantified by [18F]-fluorodeoxyglucose ([18F]-FDG) PET/CT imaging. Spearman's correlation, Kendall's tau, Kolmogorov-Smirnov test, and ANOVA were used for statistical analysis. [89Zr]-pertuzumab mean standard uptake values (SUVmean) of BT474 tumors were 4.9 ± 1.5, MDA-MB-361 tumors were 1.4 ± 0.2, and MDA-MB-231 (HER2-) tumors were 1.1 ± 0.4. [18F]-FDG SUVmean changes were negatively correlated with [89Zr]-pertuzumab SUVmean (r = -0.5887, p = 0.0030). The baseline [18F]-FDG SUVmean was negatively correlated with initial [89Zr]-pertuzumab SUVmean (r = -0.6852, p = 0.0002). This study shows PTX treatment efficacy is positively correlated with HER2 expression level in human breast cancer mouse models. Molecular imaging provides a non-invasive approach to quantify biological interactions, which will help in identifying chemotherapy responders and potentially enhance clinical decision-making.

CD4 T-cell immune stimulation of HER2 + breast cancer cells alters response to trastuzumab in vitro.

INTRODUCTION: The HER2 + tumor immune microenvironment is composed of macrophages, natural killer cells, and tumor infiltrating lymphocytes, which produce pro-inflammatory cytokines. Determining the effect of T-cells on HER2 + cancer cells during therapy could guide immunogenic therapies that trigger antibody-dependent cellular cytotoxicity. This study utilized longitudinal in vitro time-resolved microscopy to measure T-cell influence on trastuzumab in HER2 + breast cancer. METHODS: Fluorescently-labeled breast cancer cells (BT474, SKBR3, MDA-MB-453, and MDA-MB-231) were co-cultured with CD4 + T-cells (Jurkat cell line) and longitudinally imaged to quantify cancer cell viability when treated with or without trastuzumab (10, 25, 50 and 100 µg/mL). The presence and timing of T-cell co-culturing was manipulated to determine immune stimulation of trastuzumab-treated HER2 + breast cancer. HER2 and TNF-α expression were evaluated with western blot and ELISA, respectively. Significance was calculated using a two-tailed parametric t-test. RESULTS: The viability of HER2 + cancer cells significantly decreased when exposed to 25 µg/mL trastuzumab and T-cells, compared to cancer cells exposed to trastuzumab without T-cells (p = 0.01). The presence of T-cells significantly increased TNF-α expression in trastuzumab-treated cancer cells (p = 0.02). Conversely, cancer cells treated with TNF-α and trastuzumab had a similar decrease in viability as trastuzumab-treated cancer cells co-cultured with T-cells (p = 0.32). CONCLUSIONS: The presence of T-cells significantly increases the efficacy of targeted therapies and suggests trastuzumab may trigger immune mediated cytotoxicity. Increased TNF-α receptor expression suggest cytokines may interact with trastuzumab to create a state of enhanced response to therapy in HER2 + breast cancer, which has potential to reducing tumor burden.

Anti-HER2 induced myeloid cell alterations correspond with increasing vascular maturation in a murine model of HER2+ breast cancer.

BACKGROUND: Therapy targeted to the human epidermal growth factor receptor type 2 (HER2) is used in combination with cytotoxic therapy in treatment of HER2+ breast cancer. Trastuzumab, a monoclonal antibody that targets HER2, has been shown pre-clinically to induce vascular changes that can increase delivery of chemotherapy. To quantify the role of immune modulation in treatment-induced vascular changes, this study identifies temporal changes in myeloid cell infiltration with corresponding vascular alterations in a preclinical model of HER2+ breast cancer following trastuzumab treatment. METHODS: HER2+ tumor-bearing mice (N = 46) were treated with trastuzumab or saline. After extraction, half of each tumor was analyzed by immunophenotyping using flow cytometry. The other half was quantified by immunohistochemistry to characterize macrophage infiltration (F4/80), vascularity (CD31 and α-SMA), proliferation (Ki67) and cellularity (H&E). Additional mice (N = 10) were used to quantify differences in tumor cytokines between control and treated groups. RESULTS: Immunophenotyping showed an increase in macrophage infiltration 24 h after trastuzumab treatment (P ≤ 0.05). With continued trastuzumab treatment, the M1 macrophage population increased (P = 0.02). Increases in vessel maturation index (i.e., the ratio of α-SMA to CD31) positively correlated with increases in tumor infiltrating M1 macrophages (R = 0.33, P = 0.04). Decreases in VEGF-A and increases in inflammatory cytokines (TNF-α, IL-1ß, CCL21, CCL7, and CXCL10) were observed with continued trastuzumab treatment (P ≤ 0.05). CONCLUSIONS: Preliminary results from this study in a murine model of HER2+ breast cancer show correlations between immune modulation and vascular changes, and reveals the potential for anti-HER2 therapy to reprogram immunosuppressive components of the tumor microenvironment. The quantification of immune modulation in HER2+ breast cancer, as well as the mechanistic insight of vascular alterations after anti-HER2 treatment, represent novel contributions and warrant further assessment for potential clinical translation.

In vitro vascularized tumor platform for modeling tumor-vasculature interactions of inflammatory breast cancer.

Inflammatory breast cancer (IBC), a rare form of breast cancer associated with increased angiogenesis and metastasis, is largely driven by tumor-stromal interactions with the vasculature and the extracellular matrix (ECM). However, there is currently a lack of understanding of the role these interactions play in initiation and progression of the disease. In this study, we developed the first three-dimensional, in vitro, vascularized, microfluidic IBC platform to quantify the spatial and temporal dynamics of tumor-vasculature and tumor-ECM interactions specific to IBC. Platforms consisting of collagen type 1 ECM with an endothelialized blood vessel were cultured with IBC cells, MDA-IBC3 (HER2+) or SUM149 (triple negative), and for comparison to non-IBC cells, MDA-MB-231 (triple negative). Acellular collagen platforms with endothelialized blood vessels served as controls. SUM149 and MDA-MB-231 platforms exhibited a significantly (p < .05) higher vessel permeability and decreased endothelial coverage of the vessel lumen compared to the control. Both IBC platforms, MDA-IBC3 and SUM149, expressed higher levels of vascular endothelial growth factor (p < .05) and increased collagen ECM porosity compared to non-IBCMDA-MB-231 (p < .05) and control (p < .01) platforms. Additionally, unique to the MDA-IBC3 platform, we observed progressive sprouting of the endothelium over time resulting in viable vessels with lumen. The newly sprouted vessels encircled clusters of MDA-IBC3 cells replicating a key feature of in vivo IBC. The IBC in vitro vascularized platforms introduced in this study model well-described in vivo and clinical IBC phenotypes and provide an adaptable, high throughput tool for systematically and quantitatively investigating tumor-stromal mechanisms and dynamics of tumor progression.

Translating preclinical MRI methods to clinical oncology.

The complexity of modern in vivo magnetic resonance imaging (MRI) methods in oncology has dramatically changed in the last 10 years. The field has long since moved passed its (unparalleled) ability to form images with exquisite soft-tissue contrast and morphology, allowing for the enhanced identification of primary tumors and metastatic disease. Currently, it is not uncommon to acquire images related to blood flow, cellularity, and macromolecular content in the clinical setting. The acquisition of images related to metabolism, hypoxia, pH, and tissue stiffness are also becoming common. All of these techniques have had some component of their invention, development, refinement, validation, and initial applications in the preclinical setting using in vivo animal models of cancer. In this review, we discuss the genesis of quantitative MRI methods that have been successfully translated from preclinical research and developed into clinical applications. These include methods that interrogate perfusion, diffusion, pH, hypoxia, macromolecular content, and tissue mechanical properties for improving detection, staging, and response monitoring of cancer. For each of these techniques, we summarize the 1) underlying biological mechanism(s); 2) preclinical applications; 3) available repeatability and reproducibility data; 4) clinical applications; and 5) limitations of the technique. We conclude with a discussion of lessons learned from translating MRI methods from the preclinical to clinical setting, and a presentation of four fundamental problems in cancer imaging that, if solved, would result in a profound improvement in the lives of oncology patients. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1377-1392.

The effects of intravoxel contrast agent diffusion on the analysis of DCE-MRI data in realistic tissue domains.

PURPOSE: Quantitative evaluation of dynamic contrast enhanced MRI (DCE-MRI) allows for estimating perfusion, vessel permeability, and tissue volume fractions by fitting signal intensity curves to pharmacokinetic models. These compart mental models assume rapid equilibration of contrast agent within each voxel. However, there is increasing evidence that this assumption is violated for small molecular weight gadolinium chelates. To evaluate the error introduced by this invalid assumption, we simulated DCE-MRI experiments with volume fractions computed from entire histological tumor cross-sections obtained from murine studies. METHODS: A 2D finite element model of a diffusion-compensated Tofts-Kety model was developed to simulate dynamic T1 signal intensity data. Digitized histology slices were segmented into vascular (vp ), cellular and extravascular extracellular (ve ) volume fractions. Within this domain, Ktrans (the volume transfer constant) was assigned values from 0 to 0.5 min-1 . A representative signal enhancement curve was then calculated for each imaging voxel and the resulting simulated DCE-MRI data analyzed by the extended Tofts-Kety model. RESULTS: Results indicated parameterization errors of -19.1% ± 10.6% in Ktrans , -4.92% ± 3.86% in ve , and 79.5% ± 16.8% in vp for use of Gd-DTPA over 4 tumor domains. CONCLUSION: These results indicate a need for revising the standard model of DCE-MRI to incorporate a correction for slow diffusion of contrast agent. Magn Reson Med 80:330-340, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting.

BACKGROUND: Quantitative diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) have the potential to impact patient care by providing noninvasive biological information in breast cancer. PURPOSE/HYPOTHESIS: To quantify the repeatability, reproducibility, and accuracy of apparent diffusion coefficient (ADC) and T1 -mapping of the breast in community radiology practices. STUDY TYPE: Prospective. SUBJECTS/PHANTOM: Ice-water DW-MRI and T1 gel phantoms were used to assess accuracy. Normal subjects (n = 3) and phantoms across three sites (one academic, two community) were used to assess reproducibility. Test-retest analysis at one site in normal subjects (n = 12) was used to assess repeatability. FIELD STRENGTH/SEQUENCE: 3T Siemens Skyra MRI quantitative DW-MRI and T1 -mapping. ASSESSMENT: Quantitative DW-MRI and T1 -mapping parametric maps of phantoms and fibroglandular and adipose tissue of the breast. STATISTICAL TESTS: Average values of breast tissue were quantified and Bland-Altman analysis was performed to assess the repeatability of the MRI techniques, while the Friedman test assessed reproducibility. RESULTS: ADC measurements were reproducible across sites, with an average difference of 1.6% in an ice-water phantom and 7.0% in breast fibroglandular tissue. T1 measurements in gel phantoms had an average difference of 2.8% across three sites, whereas breast fibroglandular and adipose tissue had 8.4% and 7.5% average differences, respectively. In the repeatability study, we found no bias between first and second scanning sessions (P = 0.1). The difference between repeated measurements was independent of the mean for each MRI metric (P = 0.156, P = 0.862, P = 0.197 for ADC, T1 of fibroglandular tissue, and T1 of adipose tissue, respectively). DATA CONCLUSION: Community radiology practices can perform repeatable, reproducible, and accurate quantitative T1 -mapping and DW-MRI. This has the potential to dramatically expand the number of sites that can participate in multisite clinical trials and increase clinical translation of quantitative MRI techniques for cancer response assessment. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

DCE- and DW-MRI as early imaging biomarkers of treatment response in a preclinical model of triple negative breast cancer.

This work evaluates quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI) parameters as early biomarkers of response in a preclinical model of triple negative breast cancer (TNBC). The standard Tofts' model of DCE-MRI returns estimates of the volume transfer constant (Ktrans ) and the extravascular extracellular volume fraction (ve ). DW-MRI returns estimates of the apparent diffusion coefficient (ADC). Mice (n = 38) were injected subcutaneously with MDA-MB-231. Tumors were grown to approximately 275 mm3 and sorted into the following groups: saline controls, low-dose Abraxane (15 mg/kg) and high-dose Abraxane (25 mg/kg). Animals were imaged at days zero, one and three. On day three, tumors were extracted for immunohistochemistry. The positive percentage change in ADC on day one was significantly higher in both treatment groups relative to the control group (p < 0.05). In addition, the positive percentage change in Ktrans was significantly higher than controls (p < 0.05) on day one for the high-dose group and on days one and three for the low-dose group. The percentage change in tumor volume was significantly different between the high-dose and control groups on day three (p = 0.006). Histology confirmed differences at day three through reduced numbers of proliferating cells (Ki67 staining) in the high-dose group (p = 0.03) and low-dose group (p = 0.052) compared with the control group. Co-immunofluorescent staining of vascular maturity [using von Willebrand Factor (vWF) and α-smooth muscle actin (α-SMA)] indicated significantly higher vascular maturation in the low-dose group compared with the controls on day three (p = 0.03), and trending towards significance in the high-dose group compared with controls on day three (p = 0.052). These results from quantitative imaging with histological validation indicate that ADC and Ktrans have the potential to serve as early biomarkers of treatment response in murine studies of TNBC.

Trastuzumab improves tumor perfusion and vascular delivery of cytotoxic therapy in a murine model of HER2+ breast cancer: preliminary results.

To employ in vivo imaging and histological techniques to identify and quantify vascular changes early in the course of treatment with trastuzumab in a murine model of HER2+ breast cancer. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used to quantitatively characterize vessel perfusion/permeability (via the parameter K (trans) ) and the extravascular extracellular volume fraction (v e ) in the BT474 mouse model of HER2+ breast cancer (N = 20) at baseline, day one, and day four following trastuzumab treatment (10 mg/kg). Additional cohorts of mice were used to quantify proliferation (Ki67), microvessel density (CD31), pericyte coverage (α-SMA) by immunohistochemistry (N = 44), and to quantify human VEGF-A expression (N = 29) throughout the course of therapy. Longitudinal assessment of combination doxorubicin ± trastuzumab (N = 42) tested the hypothesis that prior treatment with trastuzumab will increase the efficacy of subsequent doxorubicin therapy. Compared to control tumors, trastuzumab-treated tumors exhibited a significant increase in K (trans) (P = 0.035) on day four, indicating increased perfusion and/or vessel permeability and a simultaneous significant increase in v e (P = 0.01), indicating increased cell death. Immunohistochemical and ELISA analyses revealed that by day four the trastuzumab-treated tumors had a significant increase in vessel maturation index (i.e., the ratio of α-SMA to CD31 staining) compared to controls (P < 0.001) and a significant decrease in VEGF-A (P = 0.03). Additionally, trastuzumab dosing prior to doxorubicin improved the overall effectiveness of the therapies (P < 0.001). This study identifies and validates improved perfusion characteristics following trastuzumab therapy, resulting in an improvement in trastuzumab-doxorubicin combination therapy in a murine model of HER2+ breast cancer. This data suggests properties of vessel maturation. In particular, the use of DCE-MRI, a clinically available imaging method, following treatment with trastuzumab may provide an opportunity to optimize the scheduling and improve delivery of subsequent cytotoxic therapy.

Antibody-based imaging strategies for cancer.

Although mainly developed for preclinical research and therapeutic use, antibodies have high antigen specificity, which can be used as a courier to selectively deliver a diagnostic probe or therapeutic agent to cancer. It is generally accepted that the optimal antigen for imaging will depend on both the expression in the tumor relative to normal tissue and the homogeneity of expression throughout the tumor mass and between patients. For the purpose of diagnostic imaging, novel antibodies can be developed to target antigens for disease detection, or current FDA-approved antibodies can be repurposed with the covalent addition of an imaging probe. Reuse of therapeutic antibodies for diagnostic purposes reduces translational costs since the safety profile of the antibody is well defined and the agent is already available under conditions suitable for human use. In this review, we will explore a wide range of antibodies and imaging modalities that are being translated to the clinic for cancer identification and surgical treatment.

Correlation of tumor characteristics derived from DCE-MRI and DW-MRI with histology in murine models of breast cancer.

The purpose of this work was to determine the relationship between the apparent diffusion coefficient (ADC, from diffusion-weighted (DW) MRI), the extravascular, extracellular volume fraction (ve , from dynamic contrast-enhanced (DCE) MRI), and histological measurement of the extracellular space fraction. Athymic nude mice were injected with either human epidermal growth factor receptor 2 positive (HER2+) BT474 (n = 15) or triple negative MDA-MB-231 (n = 20) breast cancer cells, treated with either Herceptin (n = 8), Abraxane (low dose n = 7, high dose n = 6), or saline (n = 7 for each cell line), and imaged using DW- and DCE-MRI before, during, and after treatment. After the final imaging acquisition, the tissue was resected and evaluated by histological analysis. H&E-stained central slices were scanned using a digital brightfield microscope and evaluated with thresholding techniques to calculate the extracellular space. For both BT474 and MDA-MB-231, the median ADC of the central slice exhibited a significantly positive correlation with the corresponding central slice extracellular space as measured by H&E (p = 0.03, p < 0.01, respectively). Median ve calculated from the central slice showed differing results between the two cell lines. For BT474, a significant correlation between ve and extracellular space was calculated (p = 0.02), while MDA-MB-231 tumors did not demonstrate a significant correlation (p = 0.64). Additionally, there was no correlation discovered between ADC and ve with either whole tumor analysis or central slice analysis (p > 0.05). While ADC correlates well with the histologically determined fraction of extracellular space, these data add to the growing body of literature that suggests that ve derived from DCE-MRI is not a reliable biomarker of extracellular space for a range of physiological conditions.

Volumetric contrast-enhanced ultrasound imaging of renal perfusion.

OBJECTIVES: To determine whether volumetric contrast-enhanced ultrasound (US) imaging has the potential to monitor changes in renal perfusion after vascular injury. METHODS: Volumetric contrast-enhanced US uses a series of planar image acquisitions, capturing the nonlinear second harmonic signal from microbubble contrast agents flowing in the vasculature. Tissue perfusion parameters (peak intensity [IPK], time to peak intensity [TPK], wash-in rate [WIR], and area under the curve [AUC]) were derived from time-intensity curve data collected during in vitro flow phantom studies and in vivo animal studies of healthy and injured kidneys. For the flow phantom studies, either the contrast agent concentration was held constant (10 µL/L) with varying volumetric flow rates (10, 20, and 30 mL/min), or the flow rate was held constant (30 mL/min) with varying contrast agent concentrations (5, 10, and 20 µL/L). Animal studies used healthy rats or those that underwent renal ischemia-reperfusion injury. Renal studies were performed with healthy rats while the transducer angle was varied for each volumetric contrast-enhanced US image acquisition (reference or 0°, 45°, and 90°) to determine whether repeated renal perfusion measures were isotropic and independent of transducer position. Blood serum biomarkers and immunohistology were used to confirm acute kidney injury. RESULTS: Flow phantom results revealed a linear relationship between microbubble concentrations injected into the flow system and the IPK, WIR, and AUC (R(2) > 0.56; P < .005). Furthermore, there was a linear relationship between volume flow rate changes and the TPK, WIR, and AUC (R(2) > 0.77; P < .005). No significant difference was found between the transducer angle during data acquisition and any of the perfusion measures (P > .60). After induction of renal ischemia-reperfusion injury in the rat animal model (n = 4), volumetric contrast-enhanced US imaging of the injured kidney revealed an initial reduction in renal perfusion compared to control animals, followed by progressive recovery of vascular function. CONCLUSIONS: Volumetric contrast-enhanced US-based renal perfusion imaging may prove clinically feasible for detecting and monitoring acute kidney injury.

PET imaging of [52 Mn]Mn-DOTATATE and [52 Mn]Mn-DOTA-JR11.

Manganese-52 is gaining interest as an isotope for PET imaging due to its desirable decay and chemical properties for radiopharmaceutical development. Somatostatin receptor 2 (SSTR2) is significantly overexpressed by neuroendocrine tumors (NETs) and is an important target for nuclear imaging and therapy. As an agonist, [68Ga]Ga-DOTATATE has demonstrated significant internalization upon interaction with receptor ligands, whereas [68Ga]Ga-DOTA-JR11(as an antagonist) exhibits limited internalization but better pharmacokinetics and increased tumor uptake. The goal of this study was to label both DOTATATE and DOTA-JR11 peptides with 52Mn in high radiochemical yields (RCY) and sufficient specific activity. A comparison of these two compounds was performed in in vitro and in vivo studies in animals with somatostatin receptor-positive xenografts to characterize differences in cell, tumor, and tissue uptake. Radiolabeling of DOTATATE and DOTA-JR11 was carried out by combining varying concentrations of the peptides with [52Mn]MnCl2. In vitro stability of the radiotracers was determined in mouse serum. In vitro cell uptake and internalization assays were performed in SSTR2 + AR42J cells and negative controls. In vivo biodistribution and longitudinal PET imaging was evaluated in mice bearing AR42J tumors. Both [52Mn]Mn-DOTATATE and [52Mn]Mn-DOTA-JR11showed affinity for SSTR2 in AR42J cells. However, the uptake of [52Mn]Mn-DOTATATE was higher (11.95 ± 0.71%/ mg) compared to [52Mn]Mn-DOTA-JR11 (7.31 ± 0.38%/ mg) after 2 h incubation. After 4 h incubation, 53.13 ± 1.83% of the total activity of [52Mn]Mn-DOTATATE was internalized, whereas only 20.85 ± 0.59% of the total activity of [52Mn]Mn-DOTA-JR11 was internalized. The PET images revealed similar biodistribution results, with [52Mn]Mn-DOTATATE showing a significant tumor uptake of 11.16 ± 2.97% ID/g, while [52Mn]Mn-DOTA-JR11 exhibited a lower tumor uptake of 2.11 ± 0.30% ID/g 4 h post-injection. The synthesis of both radiotracers was accomplished with high RCY and purity. The cell uptake and internalization of [52Mn]Mn-DOTATATE showed higher levels compared to [52Mn]Mn-DOTA-JR11. PET images of the radiotracers in AR42J tumor bearing mice demonstrated similar biodistribution in all organs except the tumor, with [52Mn]Mn-DOTATATE showing higher tumor uptake compared to [52Mn]Mn-DOTA-JR11. The variations in properties of these tracers could be used to guide further imaging and treatment studies.