Longitudinal brain volumetrics in glioma survivors.

OBJECTIVE: Radiation therapy (RT) is used selectively for patients with low-grade glioma (LGG) given the concerns for potential cognitive effects in survivors, but prior cognitive outcome studies among LGG survivors have had inconsistent findings. Translational studies that characterize changes in brain anatomy and physiology after treatment of LGG may help to both contextualize cognitive findings and improve the overall understanding of radiation effects in normal brain tissue. This study aimed to investigate the hypothesis that patients with LGG who are treated with RT will experience greater brain volume loss than those who do not receive RT. METHODS: This retrospective longitudinal study included all patients with WHO grade 2 glioma who received posttreatment surveillance MRI at the University of Alabama at Birmingham. Volumetric analysis of contralateral cortical white matter (WM), cortical gray matter (GM), and hippocampus was performed on all posttreatment T1-weighted MRI sequences using the SynthSeg script. The effect of clinical and treatment variables on brain volumes was assessed using two-level hierarchical linear models. RESULTS: The final study cohort consisted of 105 patients with 1974 time points analyzed. The median length of imaging follow-up was 4.6 years (range 0.36-18.9 years), and the median number of time points analyzed per patient was 12 (range 2-40). Resection was performed in 79 (75.2%) patients, RT was administered to 61 (58.1%) patients, and chemotherapy was administered to 66 (62.9%) patients. Age at diagnosis (ß = -0.06, p < 0.001) and use of RT (ß = -1.12, p = 0.002) were associated with the slope of the contralateral cortical GM volume model (i.e., change in GM over time). Age at diagnosis (ß = -0.08, p < 0.001), midline involvement (ß = 1.31, p = 0.006), and use of RT (ß = -1.45, p = 0.001) were associated with slope of the contralateral cortical WM volume model. Age (ß = -0.0027, p = 0.001), tumor resection (ß = -0.069, p < 0.001), use of chemotherapy (ß = -0.0597, p = 0.003), and use of RT (ß = -0.0589, p < 0.001) were associated with the slope of the contralateral hippocampus volume model. CONCLUSIONS: This study demonstrated volume loss in contralateral brain structures among LGG survivors, and patients who received RT experienced greater volume loss than those who did not. The results of this study may help to provide context for cognitive outcome research in LGG survivors and inform the design of future strategies to preserve cognition.

Volumetric brain assessment of long-term head and neck cancer survivors.

BACKGROUND: Radiation therapy (RT) for locally advanced head and neck cancer (HNC) often exposes subcortical brain structures to radiation. We performed this study to assess region-specific brain volumetrics in a population of long term HNC survivors. METHODS AND MATERIALS: Forty HNC survivors were enrolled at a mean of 6.4 years from completion of RT. Patients underwent a research MRI protocol that included a 3D T1- weighted whole-brain scan on a 3 Tesla MRI scanner. Voxel based morphometry was performed using the Computational Anatomy Toolbox with the Neuromorphometrics atlas. Healthy controls from the Human Connectome Project were used as a comparison cohort. Study participants also completed a comprehensive neurocognitive assessment. RESULTS: The final study cohort consisted of 38 participants after excluding 2 participants due to image quality. HNC survivors displayed widespread reduction in gray matter (GM) brain region volumes that included bilateral medial frontal cortex, temporal lobe, hippocampus, supplemental motor area, and cerebellum. Greater radiation exposure was associated with reduced GM volume in the left ventral diencephalon (r = -0.512, p = 0.003). Associations between cognition and regional GM volumes were identified for motor coordination and bilateral cerebellum (left, r = 0.444, p = 0.009; right, r = 0.372, p = 0.030), confrontation naming and left amygdala (r = 0.382, p = 0.026), verbal memory and bilateral thalamus (left, r = 0.435, p = 0.010; right, r = 0.424, p = 0.012), right amygdala (r = 0.339, p = 0.050), and right putamen (r = 0.364, p = 0.034). CONCLUSIONS: Reductions in GM were observed within this cohort of primarily non-nasopharyngeal HNC survivors as compared to a control sample. GM volumes were associated with performance in multiple cognitive domains. Results of this exploratory study support the need for investigation of anatomic brain changes as an important translational corollary to cognitive problems among HNC survivors.

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.

Evaluating the Accuracy of FUCCI Cell Cycle In Vivo Fluorescent Imaging to Assess Tumor Proliferation in Preclinical Oncology Models.

PURPOSE: The primary goal of this study is to evaluate the accuracy of the fluorescence ubiquitination cell cycle indicator (FUCCI) system with fluorescence in vivo imaging compared to 3'-deoxy-3'-[18F]fluorothymidine ([18F]-FLT) positron emission tomography (PET)/computed tomography (CT) and biological validation through histology. Imaging with [18F]-FLT PET/CT can be used to noninvasively assess cancer cell proliferation and has been utilized in both preclinical and clinical studies. However, a cost-effective and straightforward method for in vivo, cell cycle targeted cancer drug screening is needed prior to moving towards translational imaging methods such as PET/CT. PROCEDURES: In this study, fluorescent MDA-MB-231-FUCCI tumor growth was monitored weekly with caliper measurements and fluorescent imaging. Seven weeks post-injection, [18F]-FLT PET/CT was performed with a preclinical PET/CT, and tumors samples were harvested for histological analysis. RESULTS: RFP fluorescent signal significantly correlated with tumor volume (r = 0.8153, p < 0.0001). Cell proliferation measured by GFP fluorescent imaging was correlated with tumor growth rate (r = 0.6497, p < 0.001). Also, GFP+ cells and [18F]-FLT regions of high uptake were both spatially located in the tumor borders, indicating that the FUCCI-IVIS method may provide an accurate assessment of tumor heterogeneity of cell proliferation. The quantification of total GFP signal was correlated with the sum of tumor [18F]-FLT standard uptake value (SUV) (r = 0.5361, p = 0.0724). Finally, histological analysis confirmed viable cells in the tumor and the correlation of GFP + and Ki67 + cells (r = 0.6368, p = 0.0477). CONCLUSION: Fluorescent imaging of the cell cycle provides a noninvasive accurate depiction of tumor progression and response to therapy, which may benefit in vivo testing of novel cancer therapeutics that target the cell cycle.

[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.