Abstract
Targeted radionuclide therapy (TRT) is a rapidly advancing branch of nuclear medicine in which therapeutic radioisotopes are attached to tumor-specific molecules to deliver radiation directly to cancer cells. Among emerging isotopes, terbium-161 (¹⁶¹Tb) is highly promising due to its mixed emission of β⁻ particles, conversion electrons, and Auger electrons. This unique emission spectrum provides both millimeter-scale crossfire effects and nanometer-scale energy deposition, enhancing the therapeutic potential compared with current standards such as lutetium-177. However, the kidney remains the main dose-limiting organ because peptide-based radioligands are reabsorbed in the proximal tubules, where radiation damage can accumulate. Despite this, the microscopic and subcellular distribution of terbium and its daughter dysprosium remains largely unknown.
This PhD project aims to develop and apply advanced electron microscopy (EM) and microanalysis techniques to map terbium and dysprosium in biological tissues with micrometer to nanometer resolution. Work will focus on optimizing sample preparation (fixation, dehydration, embedding) and establishing analytical workflows for scanning (SEM/EPMA-WDS) and transmission (TEM/STEM-EDS) electron microscopy. Complementary methods such as laser ablation ICP-MS (LA-ICP-MS) and autoradiography will be used to cross-validate elemental localization. The resulting EM data will be integrated into Monte Carlo dosimetry models to quantify dose deposition across biological scales from organ and tissue to individual cell structures.
By combining expertise in radiochemistry, instrumentation, and biology, the project will bridge a crucial gap between organ-level activity measurements and nanoscale dose delivery. The developed methods will improve understanding of renal dose limitation and heterogeneous tumor response, contributing to safer and more effective TRT. The outcomes will also provide a standardized methodological framework for future studies on other therapeutic radiometals.
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