Publications by authors named "Radka Chakalova"

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 In source capable of generating the pattern.

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The interactions between energetic ions and biological and/or organic target materials have recently attracted theoretical and experimental attention, due to their implications for detector and device technologies, and for therapeutic applications. Most of the attention has focused on detection of the primary ionization tracks, and their effects, while recoil target atom tracks remain largely unexplored. Detection of tracks by a negative tone photoresist (SU-8), followed by standard development, in combination with analysis by atomic force microscopy, shows that both primary and recoil tracks are revealed as conical spikes, and can be characterized at high spatial resolution.

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Purpose: To explore poly(methyl methacrylate) (PMMA950) as an autoradiography substrate.

Materials And Methods: PMMA950 was spin coated onto a silicon substrate. Resists were exposed to either a 25 or 50 keV electron beam (e-beam) with fluences of 0.

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Evaluation of the intracellular distribution of radionuclides used for targeted radiotherapy (tRT) is essential for accurate dosimetry. Therefore, a direct and quantitative method for subcellular micro-autoradiography using radiation sensitive polymers (PMMA, UV1116 and AZ40XT) was developed. The electron exposure dose in radio-labelled cells due to Auger and internal conversion (IC) electron emissions of indium (¹¹¹In), a radionuclide currently used for tRT, was calculated using Monte Carlo (MC) simulation.

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