<p>Radionuclides decaying by electron capture or internal transition produce a large number of Auger electrons in a cascade that follows their radioactive decay. A shortlist of the most potent Auger electron-emitters has appeared in the literature including <sup>103m</sup>Rh, <sup>103</sup>Pd, <sup>111</sup>In, <sup>119</sup>Sb, <sup>123</sup>I, <sup>125</sup>I, <sup>165</sup>Er, and <sup>197</sup>Hg. Among them, <sup>119</sup>Sb has been identified as the most potent for targeting micrometastases, yielding several tens of Auger electrons per decay with energies from a few eV up to 30 keV. In this paper, we recalculate Auger, Coster-Kronig, and super Coster-Kronig yields and transition probabilities as subshell-normalized relative transition probabilities and develop a new method to create radionuclide sources in TOPAS Monte Carlo, the code for which has been made publicly available. We then apply our method to encode the Auger electron spectra of <sup>119</sup>Sb from MIRD RADTABS and EADL into TOPAS and calculate the absorbed dose to water volumes of radius 10 nm up to 10 μm, finding that the averaged MIRD Auger electron spectrum underestimates the absorbed dose by a factor of 20 to 50 on this scale. We show that this result is not isolated to <sup>119</sup>Sb and conclude that either the cascaded MIRD or EADL spectrum should be used for accurate microscale dosimetry. We compare with results obtained using the built-in Geant4 Atomic Relaxation for <sup>119</sup>Sb in TOPAS and find an unexpected continuum of low-energy electrons but no excess absorbed dose relative to either MIRD or EADL. We show that 119Sb does not produce more absorbed dose in microscale volumes than <sup>103m</sup>Rh, <sup>103</sup>Pd, <sup>111</sup>In, <sup>123</sup>I, <sup>125</sup>I, <sup>165</sup>Er, or <sup>197</sup>Hg, warranting future microdosimetry calculations of RBE and DNA damage to understand whether <sup>119</sup>Sb is the most potent Auger electron-emitter, as claimed in the literature.</p>
Funding
AVZ is supported by an Ontario Graduate Scholarship and funding from the Faculty of Science (FOS) at Toronto Metropolitan University (TMU). EDS acknowledges funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) in the form of a Discovery Grant as well as the FOS at TMU for financial support of this research. JG acknowledges funding in the form of an NSERC Discovery Grant and financial support from the FOS at TMU.