Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
A Road Map for Computational Surgery: Challenges and Opportunities Kapitel lesen Erstes Kapitel lesen

2014 | OriginalPaper | Buchkapitel

19. Some Models for the Prediction of Tumor Growth: General Framework and Applications to Metastases in the Lung

verfasst von : Thierry Colin, Angelo Iollo, Damiano Lombardi, Olivier Saut, Françoise Bonichon, Jean Palussière

Erschienen in: Computational Surgery and Dual Training

Verlag: Springer New York

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This chapter presents an example of an application of a mathematical model: the goal is here to help clinicians evaluate the aggressiveness of some metastases to the lung. For this matter, an adequate spatial model is described and two algorithms (one using a reduced model approach and the other one a sensitivity technique) are shown. They allow us to find reasonable values of the parameters of this model for a given patient with a sequence of medical images. The quality of the prognosis obtained through the calibrated model is then illustrated with several clinical cases.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Transport in Nanoconfinement and Within Blood Vessel Wall
Nächstes Kapitel Quantifying the Role of Anisotropic Invasion in Human Glioblastoma
Literatur
1.
Alarcón T, Byrne H, Maini P (2003) A cellular automaton model for tumour growth in inhomogeneous environment. J Theor Biol 225(2):257–274CrossRef
2.
Ambrosi D, Preziosi L (2002) On the closure of mass balance models for tumor growth. Math Models Meth Appl Sci 12(05):737–754MathSciNetCrossRefMATH
3.
Anderson ARA, Weaver AM, Cummings PT, Quaranta V (2006) Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment. Cell 127(5): 905–915CrossRef
4.
5.
Billy F, Ribba B, Saut O, Morre-Trouilhet H, Colin T, Bresch D, Boissel J-P, Grenier E, Flandrois J (2009) A pharmacologically based multiscale mathematical model of angiogenesis and its use in investigating the efficacy of a new cancer treatment strategy. J Theor Biol 260(4):545–562. doi:10.1016/j.jtbi.2009.06.026MathSciNetCrossRef
6.
Bresch D, Colin T, Grenier E, Ribba B, Saut O (2009) A viscoelastic model for avascular tumor growth. Discrete Contin Dyn Syst Suppl 2009, 101–108MathSciNetMATH
7.
Byrd RH, Nocedal J, Schnabe RB (1994) Representations of quasi-Newton matrices and their use in limited memory methods. Math Program 63:129–156CrossRefMATH
8.
Byrne H, Drasdo D (2009) Individual-based and continuum models of growing cell populations: a comparison. J Math Biol 58(4–5):657–687MathSciNetCrossRef
9.
Byrne HM (2010) Dissecting cancer through mathematics: from the cell to the animal model. Nat Rev Cancer 10(3):221–230CrossRef
10.
Clatz O, Sermesant M, Bondiau P-Y, Delingette H, Warfield SK, Malandain G, Ayache N (2005) Realistic simulation of the 3-d growth of brain tumors in mr images coupling diffusion with biomechanical deformation. IEEE Trans Med Imaging 24(10):1334–1346CrossRef
11.
Friedman A (2004) A hierarchy of cancer models and their mathematical challenges. Discrete Contin Math Syst Ser B 4(1):147–160CrossRefMATH
12.
Gatenby R, Gawlinski ET (1996) A reaction-diffusion model of cancer invasion. Cancer Res 56(24):5745–5753
13.
Hahnfeldt P, Panigrahy D, Folkman J, Hlatky L (1999) Tumor development under angiogenic signaling. Cancer Res 59(19):4770
14.
Hanahan D, Weinberg R (2000) The hallmarks of cancer. Cell 100(1):57–70CrossRef
15.
Hanke M (1997) A regularizing Levenberg-Marquardt scheme with applications to inverse groundwater filtration problems. Inverse Probl 13:79–95MathSciNetCrossRefMATH
16.
Hogea C, Davatzikos C, Biros G (2008) An image-driven parameter estimation problem for a reaction–diffusion glioma growth model with mass effects. J Math Biol 56(6):793–825MathSciNetCrossRefMATH
17.
Holmes P, Lumley JL, Berkooz G (1996) Turbulence, coherent structures, dynamical systems and symmetry. Cambridge monographs on mechanics. Cambridge University Press, CambridgeCrossRefMATH
18.
Macklin P, Lowengrub JS (2005) Evolving interfaces via gradients of geometry-dependent interior poisson problems: application to tumor growth. J Comput Phys 203(1):191–220MathSciNetCrossRefMATH
19.
Mansury Y, Kimura M, Lobo J, Deisboeck T (2002) Emerging patterns in tumor systems: simulating the dynamics of multicellular clusters with an agent-based spatial agglomeration model. J Theor Biol 219(3):343–370MathSciNetCrossRef
20.
21.
Marzouk YM, Najm HN (2009) Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems. J Comput Phys 228(6):1862–1902MathSciNetCrossRefMATH
22.
Othmer HG, Stevens A (1997) Aggregation, blowup, and collapse: the ABC’s of taxis in reinforced random walks. SIAM J Appl Math 57(4):1044–1081MathSciNetCrossRefMATH
23.
24.
Ribba B, Saut O, Colin T, Bresch D, Grenier E, Boissel J-P (2006) A multiscale mathematical model of avascular tumor growth to investigate the therapeutic benefit of anti-invasive agents. J Theor Biol 243(4):532–541MathSciNetCrossRef
25.
Robbins RJ, Wan Q, Grewal RK, Reibke R, Gonen M, Strauss HW, Tuttle RM, Drucker W, Larson SM (2006) Real-time prognosis for metastatic thyroid carcinoma based on 2-[18F]fluoro-2-deoxy-D-glucose-positron emission tomography scanning. J Clin Endocrinol Metab 91(2):498–505CrossRef
26.
27.
Sachs LR, Hahnfeldt P (2001) Simple ODE models of tumor growth and anti-angiogenic or radiation treatment. Math Comput Model 33(12–13):1297–1305MathSciNetCrossRefMATH
28.
Schlumberger M, Sherman SI (2009) Clinical trials for progressive differentiated thyroid cancer: patient selection, study design, and recent advances. Thyroid 19(12):1393–1400CrossRef
29.
30.
Shiraishi F, Tomita T, Iwata M, Berrada AA, Hirayama H (2009) A reliable taylor series-based computational method for the calculation of dynamic sensitivities in large-scale metabolic reaction systems: algorithm and software evaluation. Math Biosci 222:73–85MathSciNetCrossRefMATH
31.
Simeoni M, Magni P, Cammia C, De Nicolao G, Croci V, Pesenti E, Germani M, Poggesi I, Rocchetti M (2004) Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents. Cancer Res 64(3): 1094–1101CrossRef
32.
33.
Swanson KR, Alvord EC, Murray JD (2002) Quantifying efficacy of chemotherapy of brain tumors with homogeneous and heterogeneous drug delivery. Acta Biotheor 50(4):223–237CrossRef
34.
Metadaten
Titel
Some Models for the Prediction of Tumor Growth: General Framework and Applications to Metastases in the Lung
verfasst von
Thierry Colin
Angelo Iollo
Damiano Lombardi
Olivier Saut
Françoise Bonichon
Jean Palussière
Copyright-Jahr
2014
Verlag
Springer New York
Buch
Computational Surgery and Dual Training

Print ISBN: 978-1-4614-8647-3

Electronic ISBN: 978-1-4614-8648-0

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-1-4614-8648-0_19

Neuer Inhalt

    Bildnachweise