A5086875206- MRI in cancer diagnosis
- Radiomics and Machine Learning in Medical Imaging
- Mathematical Biology Tumor Growth
- Medical Imaging Techniques and Applications
- HER2/EGFR in Cancer Research
- Angiogenesis and VEGF in Cancer
- Cancer Genomics and Diagnostics
- Cancer, Hypoxia, and Metabolism
- Antimicrobial Resistance in Staphylococcus
- Breast Cancer Treatment Studies
- Single-cell and spatial transcriptomics
- Monoclonal and Polyclonal Antibodies Research
- Advanced MRI Techniques and Applications
- Immune cells in cancer
- Cancer Cells and Metastasis
- Glioma Diagnosis and Treatment
- HIV/AIDS Research and Interventions
- Gene Regulatory Network Analysis
- Radiopharmaceutical Chemistry and Applications
- Bioinformatics and Genomic Networks
- Advanced Neuroimaging Techniques and Applications
- Immune Response and Inflammation
- Cancer Immunotherapy and Biomarkers
- Veterinary medicine and infectious diseases
- Adolescent Sexual and Reproductive Health
The University of Texas at Austin
2017-2024
Livestrong Foundation
2018-2023
Florida State University
2014-2016
Triple-negative breast cancer (TNBC) is persistently refractory to therapy, and methods improve targeting evaluation of responses therapy in this disease are needed. Here, we integrate quantitative MRI data with biologically based mathematical modeling accurately predict the response TNBC neoadjuvant systemic (NAST) on an individual basis. Specifically, 56 patients enrolled ARTEMIS trial (NCT02276443) underwent standard-of-care doxorubicin/cyclophosphamide (A/C) then paclitaxel for NAST,...
The ability to accurately predict response and then rigorously optimize a therapeutic regimen on patient-specific basis, would transform oncology. Toward this end, we have developed an experimental-mathematical framework that integrates quantitative magnetic resonance imaging (MRI) data into biophysical model treatment of locally advanced breast cancer neoadjuvant therapy. Diffusion-weighted dynamic contrast-enhanced MRI is collected prior therapy, after 1 cycle at the completion first...
Background Quantitative diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced (DCE-MRI) have the potential to impact patient care by providing noninvasive biological information in breast cancer. Purpose/Hypothesis To quantify repeatability, reproducibility, accuracy of apparent diffusion coefficient (ADC) T1-mapping community radiology practices. Study Type Prospective. Subjects/Phantom Ice-water DW-MRI T1 gel phantoms were used assess accuracy. Normal subjects (n = 3) across three...
The goal of this study is to experimentally and computationally investigate combination trastuzumab-paclitaxel therapies identify potential synergistic effects due sequencing the with in vitro imaging mathematical modeling. Longitudinal alterations cell confluence are reported for an model BT474 HER2+ breast cancer cells following various dosages timings paclitaxel trastuzumab regimens. Results drug regimens evaluated interaction relationships based on order, timing, quantity dose drugs....
Clinical methods for assessing tumor response to therapy are largely rudimentary, monitoring only temporal changes in size. Our goal is predict the of breast tumors using a mathematical model that utilizes magnetic resonance imaging (MRI) data obtained non-invasively from individual patients. We extended previously established, mechanically coupled, reaction-diffusion predicting initialized with patient-specific diffusion weighted MRI (DW-MRI) by including effects chemotherapy drug delivery,...
Abstract The goal of this study is to develop an integrated, mathematical–experimental approach for understanding the interactions between immune system and effects trastuzumab on breast cancer that overexpresses human epidermal growth factor receptor 2 (HER2+). A coupled, ordinary differential equations was constructed describe temporal changes in tumour growth, along with intratumoural response, vascularity, necrosis hypoxia. mathematical model calibrated serially acquired experimental...
Abstract While targeted therapies exist for human epidermal growth factor receptor 2 positive (HER2 +) breast cancer, HER2 + patients do not always respond to therapy. We present the results of utilizing a biophysical mathematical model predict tumor response two cancer treated with same therapeutic regimen but who achieved different treatment outcomes. Quantitative data from magnetic resonance imaging (MRI) and 64 Cu-DOTA-trastuzumab positron emission tomography (PET) are used estimate...
Abstract Background Intra-and inter-tumoral heterogeneity in growth dynamics and vascularity influence tumor response to radiation therapy. Quantitative imaging techniques capture these non-invasively, data can initialize constrain predictive models of on an individual basis. Methods We have developed a family 10 biologically-based mathematical describing the spatiotemporal volume fraction, blood To evaluate this models, rats ( n = 13) with C6 gliomas were imaged magnetic resonance (MRI)...
This study establishes a fluid dynamics model personalized with patient-specific imaging data to optimize neoadjuvant therapy (i.e., doxorubicin) protocols for breast cancers.
Upon recognition of auto-antigens, thymocytes are negatively selected or diverted to a regulatory T cell (Treg) fate. CCR7 is required for negative selection auto-reactive in the thymic medulla. Here, we describe an unanticipated contribution intrathymic Treg generation. Ccr7−/− mice have increased cellularity because hematopoietic but non-T autonomous function. expression by dendritic cells (DCs) promotes survival mature Sirpα− DCs. Thus, deficiency results apoptosis DCs, which...
KEYWORDS: Computational oncologyMRItreatment responseoptimal control theoryradiation therapychemotherapy
A significant challenge in the field of biomedicine is development methods to integrate multitude dispersed data sets into comprehensive frameworks be used generate optimal clinical decisions. Recent technological advances single cell analysis allow for high-dimensional molecular characterization cells and populations, but date, few mathematical models have attempted measurements from scale with other types longitudinal data. Here, we present a framework that actionizes static outputs...
Abstract Purpose To develop and validate a mechanism-based, mathematical model that characterizes 9L C6 glioma cells’ temporal response to single-dose radiation therapy in vitro by explicitly incorporating time-dependent biological interactions with radiation. Methods We employed time-resolved microscopy track the confluence of cells receiving doses 0, 2, 4, 6, 8, 10, 12, 14 or 16 Gy. DNA repair kinetics are measured γH2AX expression via flow cytometry. The data (814 replicates for 9L, 540...
Abstract Background Therapy targeted to the human epidermal growth factor receptor type 2 (HER2) is used in combination with cytotoxic therapy treatment of HER2+ breast cancer. Trastuzumab, a monoclonal antibody that targets HER2, has been shown pre-clinically induce vascular changes can increase delivery chemotherapy. To quantify role immune modulation treatment-induced changes, this study identifies temporal myeloid cell infiltration corresponding alterations preclinical model cancer...
Fractionated radiation therapy is central to the treatment of numerous malignancies, including high-grade gliomas where complete surgical resection often impractical due its highly invasive nature. Development approaches forecast response fractionated may provide ability optimize or adapt plans for radiotherapy. Towards this end, we have developed a family 18 biologically-based mathematical models describing both tumor and vasculature therapy. Importantly, these can be personalized...