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PHYSICAL REVIEW E 80, 051910 共2009兲 Growing heterogeneous tumors in silico Jana Gevertz1,* and S. Torquato1,2,3,4,5,† 1
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Document Date: 2009-11-17 09:42:59

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Ewing / /

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United States / /

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Princeton University / The College of New Jersey / Princeton Institute / /

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Medical imaging technologies / constrained algorithm / discussed algorithms / clinical applications / magnetic resonance imaging / 2D cancer simulation tool / cancer simulation tool / host blood vessel network / growth algorithm / merged cancer simulation tool / healthy capillary network / disorganized angiogenic blood vessel network / biophysical tools / blood vessel network / individual algorithm / proposed simulation tool / described algorithms / merged algorithm / vascular network / microvascular network / silico tool / present algorithm / vascular algorithm / simulation tool / potential clinical applications / computational tool / capillary network / confined growth algorithm / constrained growth algorithm / computational algorithm / tumor growth algorithm / cell site / given cell site / /

MedicalCondition

A. Simulating tumor / neoplasms / main tumor / merged cancer / original tumor / mutant tumor / strain / spherically symmetric tumor / glioma growth / necrotic tumor / metastasis / human tumor / simulated tumor / proliferative cancer / proliferative tumor / radially symmetric tumor / human adenocarcinoma cells / spinal cord tumors / hypoxic tumor / 2D cancer / each tumor / tumor’s / each patient’s tumor / actual tumor / comprehensive cancer / both predicting tumor / glioblastoma / individual tumor / dissociation / real tumors / Hf I. INTRODUCTION Cancer / cancers / tumor / necrosis / cancer / tumors / neoplasm / relevant previous tumor / final tumor / glioblastoma multiforme / volumetric tumor / circular tumors / clinically relevant cancer / glioblastomas / TP53 tumor / heterogeneous tumors / V. DISCUSSION The cancer / single cancer / aggressive tumor / mass tumor / single tumor / actual tumors / diseases / metastases / /

MedicalTreatment

multimodal treatment / /

Organization

Institute for Advanced Study / Princeton University / Princeton Institute for the Science and Technology of Materials / U.S. Securities and Exchange Commission / Department of Mathematics and Statistics / Department of Chemistry / College of New Jersey / Princeton Center for Theoretical Science / School of Natural Sciences / /

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S. TORQUATO / S. TORQUATO FIG / JANA GEVERTZ / /

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Dv / /

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C + + / /

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New Jersey / /

Technology

Medical imaging technologies / present algorithm / MODEL BACKGROUND The algorithm / tomography / CA algorithm / cell signaling / confined growth algorithm / tumor growth algorithm / vascular algorithm / apoptosis / MRI / environmentally constrained growth algorithm / previously discussed algorithms / magnetic resonance imaging / previously described algorithms / gene expression / merged algorithm / simulation / individual algorithm / Technology of Materials / computational algorithm / environmentally constrained algorithm / /

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