Abstract
We investigated the generation of proton- and alpha-induced nuclear cross-section data in the production of Indium-111 (111In) for application in nuclear medicine. Here, we are interested in three reaction channels, which are 109Ag (α, 2n), 111Cd (p, n) and 112Cd (p, 2n), in the production of 111In. A random forest algorithm was used to generate nuclear cross-section data by using an experimental nuclear cross-section from the Experimental Nuclear Reaction Data (EXFOR) database as input. Hence, reasonably accurate regression curves of nuclear cross-section data could be produced with the evaluated nuclear data library ENDF/B-VII.0 set as the benchmark.
Highlights
Nuclear reaction cross-section data are very important to the field of medical radiobiology in both diagnostic imaging and targeted therapy for cancer treatment because they can be used to optimize established and new nuclear reaction routes, which is crucial for the optimization of the production of radionuclide [1]
Since the models of our machine learning depend on the number and combination of predictors, estimators such as correlation coefficient (R2 ) and the root mean square error (RMSE) can be the benchmark to evaluate the performance of our machine learning
We have studied the performance of a random forest (RF) machine learning algorithm in generating nuclear cross-section data for 109 Ag (α, 2n) 111 In, 111 Cd (p, n) 111 In and 112 Cd (p, 2n) 111 In nuclear reactions
Summary
Nuclear reaction cross-section data are very important to the field of medical radiobiology in both diagnostic imaging and targeted therapy for cancer treatment because they can be used to optimize established and new nuclear reaction routes, which is crucial for the optimization of the production of radionuclide [1]. 68 Zn (p, 2p) 67 Cu could be achieved by using incident proton energy-operable in-house medical cyclotron. Another example is that 72 As can be used in theranostic therapy, in positron emission tomography (PET). Other than proton-induced nuclear reaction, muon capture has previously been used in the production of various useful radionuclides such as technetium-99m, which is the decay product of molybdenum-99 [3]
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