Francisco Gimenez

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Optimal results in the direct brain delivery of brain therapeutics such as growth factors or viral vector into primate brain depend on reproducible distribution throughout the target region. In the present study, we retrospectively analyzed MRI of 25 convection-enhanced delivery (CED) infusions with MRI contrast into the putamen of non-human primates (NHP).(More)
Recently, we developed an MRI-based method that enables tracking of parenchymal infusions of therapeutic agents by inclusion of a contrast reagent in the infusate. We show that both liposomal Gadoteridol (GDL) and free Gadoteridol (Gd) can be used for MRI-monitored infusions into the non-human primate (NHP) putamen to predict the distribution of GDNF(More)
BACKGROUND Real-time convection-enhanced delivery (RCD) of adeno-associated viral vectors by co-infusion of gadoteridol allows T1 magnetic resonance imaging (T1 MRI) prediction of areas of subsequent gene expression. The use of T2 MRI in RCD is less developed. In addition, the effect of flushing a dead-space volume on subsequent distribution of a(More)
We aim to predict radiological observations using computationally-derived imaging features extracted from computed tomography (CT) images. We created a dataset of 79 CT images containing liver lesions identified and annotated by a radiologist using a controlled vocabulary of 76 semantic terms. Computationally-derived features were extracted describing(More)
This study presents a computational tool for auto-segmenting the distribution of brain infusions observed by magnetic resonance imaging. Clinical usage of direct infusion is increasing as physicians recognize the need to attain high drug concentrations in the target structure with minimal off-target exposure. By co-infusing a Gadolinium-based contrast agent(More)
OBJECTIVE To evaluate a system we developed that connects natural language processing (NLP) for information extraction from narrative text mammography reports with a Bayesian network for decision-support about breast cancer diagnosis. The ultimate goal of this system is to provide decision support as part of the workflow of producing the radiology report.(More)
1. Introduction Liver lesions stem from a variety of causes ranging from benign to malignant. The ability to efficiently and accurately differentiate these lesions as malignant or benign using non-invasive medical imaging is important to patient treatment and outcome. Contrast-enhanced computed tomography (CT) imaging is the dominant technology used for(More)
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