A stochastic model of cell survival for high‐Z nanoparticle radiotherapy. Issue 2 (14th January 2013)

• Record Type: Journal Article
• Authors: Zygmanski, Piotr; Hoegele, Wolfgang; Tsiamas, Panagiotis; Cifter, Fulya; Ngwa, Wil; Berbeco, Ross; Makrigiorgos, Mike; Sajo, Erno
• Is Part Of: Medical physics. Volume 40:Issue 2(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-01-14
• Subjects: Therapeutic applications, including brachytherapy -- Nanotechnologies‐applications -- Subcellular structure and processes; cellular effects of radiation -- gold -- nanomedicine -- nanoparticles -- radiation therapy -- stochastic processes; gold -- nanoparticle -- LEM -- RBE; Radiation therapy -- Nano‐structures; Dosimetry -- Nanoparticles -- DNA -- Probability theory -- Cancer -- Cell membranes -- X‐ray effects -- Radiation therapy -- Gold -- Numerical modeling; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4773885
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : The authors present a stochastic framework for the assessment of cell survival in gold nanoparticle radiotherapy. Methods: : The authors derive the equations for the effective macroscopic dose enhancement for a population of cells with nonideal distribution of gold nanoparticles (GNP), allowing different number of GNP per cell and different distances with respect to the cellular target. They use the mixed Poisson distribution formalism to model the impact of the aforementioned physical factors on the effective dose enhancement. Results: : The authors show relatively large differences in the estimation of cell survival arising from using approximated formulae. They predict degeneration of the cell killing capacity due to different number of GNP per cell and different distances with respect to the cellular target. Conclusions: : The presented stochastic framework can be used in interpretation of experimental cell survival or tumor control probability studies.