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Updated: Mar 15, 2026

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Published on: February 1, 2018
Internalization of Auger electron-emitting isotopes into cancer cells: a method for spatial distribution
Georgina Royle1, Nadia Falzone1,2, Radka Chakalova3
1a CRUK/MRC Oxford Institute for Radiation Oncology, Department of Oncology , University of Oxford , Oxford , UK.
Purpose:
A challenge for single-cell dosimetry of internalized Auger electron-emitting (AE) radiopharmaceuticals remains how best to elucidate their spatial distribution. To this end, a method, photoresist autoradiography (PAR), was previously developed to identify the lateral spatial distribution of AE-emitting radionuclides internalized in single cancer cells. In this paper, we present a simple mathematical model based on the radius and depth of radiation-induced patterns in photoresist material to identify the location in the z-plane of an 111In source capable of generating the pattern.
Materials And Methods:
SQ20B cells, derived from a head and neck squamous cell carcinoma, were exposed to 111In-labeled epidermal growth factor (EGF) (8 MBq/microg). The integrated electron fluence after four half-lives from the internalized radionuclide-containing construct was detected by a photoresist layer that was placed in close proximity to the cells. The resultant latent patterns were chemically developed and analyzed by atomic force microscopy (AFM). The features in the patterns were matched to locations of electrons emitted from simulated point sources, thereby determining the likely locations of internalized radionuclides.
Results:
The modeling procedure was validated using simple patterns. The model relates the depth and radius (in the x-y plane) of a pattern to the location and fluence of the source giving rise to the pattern. This point source modeling method provided a good fit to experimental data and can be expanded to analyze more complex patterns.
Conclusions:
We have demonstrated the utility of the modelling technique to identify the location of internalized AE-emitting radionuclides. This methodology now needs to be extended to predict the source positions in more complex PAR patterns.
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