TH-C-213AB-09: State-Driven Mathematical Model Simulations of Tumor Response to Radiotherapy: How Does High FDG Uptake Relate to Classical Radiobiological Principles?

2012 ◽  
Vol 39 (6Part30) ◽  
pp. 3995-3995
Author(s):  
J Jeong ◽  
J O Deasy
Keyword(s):  
Mathematical Model ◽  
Tumor Response ◽  
Model Simulations ◽  
Fdg Uptake

The ancient Lake Albano tunnel: origins and considerations regarding the hydraulic regulation achieved

2007 ◽  
Vol 7 (1) ◽  
pp. 269-276
Author(s):  
R. Drusiani ◽  
P. Bersani ◽  
P. Penta
Keyword(s):  
Mathematical Model ◽  
Ancient Lake ◽  
Model Simulations ◽  
Volcanic Lakes ◽  
Colli Albani ◽  
Atmospheric Phenomena

A brief description of the geomorphological, historical, and archaeological aspects of the Colli Albani area, where the volcanic lakes of Albano and Nemi are situated, is followed by an examination on the problem of the policies of lake Albano regulation, by means of an ancient tunnel dating at least to the 5th century BC. In particular, it is investigated how, in the presence of even severe atmospheric phenomena, it was possible to control fluctuations in the level of the lake on the banks of which there were large settlements. Mathematical model simulations indicate the effectiveness of the ancient tunnel in achieving these objectives.

scholarly journals Predicting pathologic tumor response to chemoradiotherapy with histogram distances characterizing longitudinal changes in 18 F-FDG uptake patterns

2013 ◽  
Vol 40 (10) ◽  
pp. 101707 ◽  
Author(s):  
Shan Tan ◽  
Hao Zhang ◽  
Yongxue Zhang ◽  
Wengen Chen ◽  
Warren D. D'Souza ◽  
...  
Keyword(s):  
Tumor Response ◽  
Longitudinal Changes ◽  
Fdg Uptake

scholarly journals Adaptive Mathematical Model of Tumor Response to Radiotherapy Based on CBCT Data

2016 ◽  
Vol 20 (3) ◽  
pp. 802-809 ◽  
Author(s):  
A. Belfatto ◽  
M. Riboldi ◽  
D. Ciardo ◽  
A. Cecconi ◽  
R. Lazzari ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Tumor Response

Ouabain modulation of cellular calcium stores and signaling

2007 ◽  
Vol 293 (5) ◽  
pp. F1518-F1532 ◽  
Author(s):  
Aurélie Edwards ◽  
Thomas L. Pallone
Keyword(s):  
Mathematical Model ◽  
Sarcoplasmic Reticulum ◽  
Active Transport ◽  
Intracellular Localization ◽  
Calcium Stores ◽  
Model Simulations ◽  
Store Depletion ◽  
Intracellular Ca ◽  
Atpase Inhibition ◽  
Predominant Effect

Ouabain-like factors modulate intracellular Ca2+ concentrations and Ca2+ stores. Recently, a role for Na+-K+-ATPase Na+ transport inhibition as a pivotal event in ouabain signaling was questioned (Kaunitz JD. Am J Physiol Renal Physiol 290: F995–F996, 2006). In the present study, we used a mathematical model of Ca2+ trafficking in cytoplasm and subplasmalemmal microdomains to simulate the pathways through which ouabain can affect Ca2+ signaling: inhibition of active transport by Na+-K+-ATPase α1- and α2-isoforms, activation of inositol trisphosphate (IP3) production, and increased IP3 receptor (IP3R) conductance. A fundamental prediction is that Na+-K+-ATPase inhibition favors sarcoplasmic reticulum Ca2+ store loading, whereas Src-mediated increases in IP3 production and IP3R sensitization favor store depletion. The model predicts that α2-isoform inhibition generates a peak-and-plateau pattern of cytosolic Ca2+ concentration ([Ca2+]cyt) elevation, whereas α1-isoform inhibition yields a monophasic rise. The effects of ouabain-mediated increases in IP3 production or IP3R conductance on [Ca2+]cyt depend on their relative distributions between cellular microdomains and the bulk cytoplasm. Simulations suggest that the intracellular localization of IP3 production is a pivotal determinant of the changes in compartmental Ca2+ concentrations that can be induced by ouabain. As a consequence of sequestration of the ouabain-sensitive α2-isoform into microdomains, inhibition of the α2-isoform in rodents is not predicted to significantly affect cytosolic Na+ concentration. Model simulations support the hypothesis that ouabain can enhance agonist-evoked [Ca2+]cyt transients when its predominant effect is to inhibit α2-isoform Na+ transport and, thereby, increase Ca2+ loading into sarcoplasmic reticulum stores.

scholarly journals A mathematical model for brain tumor response to radiation therapy

2008 ◽  
Vol 58 (4-5) ◽  
Author(s):  
R. Rockne ◽  
E. C. Alvord ◽  
J. K. Rockhill ◽  
K. R. Swanson
Keyword(s):  
Mathematical Model ◽  
Radiation Therapy ◽  
Brain Tumor ◽  
Tumor Response

Analysis of anticancer efficiency of combined fractionated radiotherapy and antiangiogenic therapy via mathematical modelling

2018 ◽  
Vol 33 (4) ◽  
pp. 225-242 ◽  
Author(s):  
Maxim B. Kuznetsov ◽  
Vladimir V. Gubernov ◽  
Andrey V. Kolobov
Keyword(s):  
Mathematical Model ◽  
Antiangiogenic Therapy ◽  
Combined Treatment ◽  
Palliative Therapy ◽  
Nutrient Deprivation ◽  
Curative Effect ◽  
Model Simulations ◽  
Fractionated Radiotherapy ◽  
Spatially Distributed ◽  
Preclinical And Clinical Studies

Abstract One of the relatively new modalities in treatment of cancer is antiangiogenic therapy (AAT), which stops the formation of new blood vessels, thus leading to nutrient deprivation of a tumor. It has been discovered that it can cause transient alleviation of intratumoral hypoxia, which has induced interest in investigation of its combination with radiotherapy (RT), since presence of oxygen stimulates efficiency of the latter. Preclinical and clinical studies have shown ambiguous results concerning such combined treatment, indicating a need for theoretical investigation. For that purpose, we have developed a spatially-distributed mathematical model of tumor growth and combined RT with AAT. Model simulations in a physiologically justified range of parameters suggest that outcome of addition of AAT to RT should depend on the tumor radiosensitivity: under its low values, when RT de facto serves as a palliative therapy, inclusion of AAT may prolong patient’s survival; however, under high tumor radiosensitivity, AAT may compromise curative effect of RT.

scholarly journals FPtool a software tool to obtain in silico genotype-phenotype signatures and fingerprints based on massive model simulations

2018 ◽  
Author(s):  
Guido Santos ◽  
Julio Vera
Keyword(s):  
Mathematical Model ◽  
In Silico ◽  
Software Tool ◽  
Biochemical Network ◽  
Qualitative Behaviour ◽  
Model Simulations

Fptool is an intuitive tool that provides to the user a preliminary fingerprint of the behaviour simulated by a mathematical model of a biochemical network when comparing two biological scenarios defined by the user. Here we present the tool and we applied to an already published mathematical model of lung legionella infection. The fingerprint obtained correlates with the results obtained in the original article. This tool is optimal for the users that would like to obtain a fast and preliminary view of the qualitative behaviour of a mathematical model before deciding for more elaborate analyses.

Mathematical Models of Cancer Evolution and Cure

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. SCI-54-SCI-54
Author(s):  
Franziska Michor
Keyword(s):  
Mathematical Model ◽  
Multiple Myeloma ◽  
Tumor Cell ◽  
Progenitor Cells ◽  
Rational Design ◽  
Tumor Response ◽  
Conflicts Of Interest ◽  
Large Set ◽  
Newly Diagnosed ◽  
Differentiated Cells

Abstract Since the pioneering work of Salmon and Durie, the availability of a quantitative measure of malignant cell burden in multiple myeloma has been used to make clinical predictions and to model tumor cell growth. Here, we analyzed a large set of tumor response data from three randomized controlled clinical trials (total sample size n=1,469 evaluable patients) to establish and validate a novel mathematical model of MM cell dynamics based on responses to bortezomib-based chemotherapy regimens. Dynamics of treatment response in newly diagnosed patients were most consistent with a mathematical model postulating the existence of two tumor cell subpopulations, "myeloma progenitor cells" and "myeloma differentiated cells". Differential treatment responses were observed with significant tumoricidal effects on myeloma differentiated cells and less clear effects on myeloma progenitor cells. We validated this model using a second trial of newly diagnosed MM patients and a third trial of refractory patients. When applying our model to data of relapsed MM patients, we found that a hybrid mathematical model incorporating both a MM differentiation hierarchy and clonal evolution best explains the tumor response patterns in all patients. The clinical data, together with mathematical modeling, suggest that bortezomib-based therapy exerts a selection pressure on myeloma cells that can shape the disease phenotype, thereby generating further inter-patient variability. This model may be a useful tool for improving the rational design of chemotherapy regimens in multiple myeloma. Disclosures No relevant conflicts of interest to declare.

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