The Monte Carlo neutron-photon transport code MCNP has been used to design a system for thermal neutron activation analysis (TNAA) of aluminium (Al) concentration in the bones of the hand. The clinical motivation for the work is the need for a non-invasive technique for the measurement of Al body burden in patients with chronic renal failure. It is necessary to moderate the high (≈ 75%) proportion of fast neutrons present in the un-moderated source spectrum. This serves to improve the gamma-ray yield from the thermal neutron induced <SUP>27</SUP>Al(n,γ)<SUP>28</SUP>Al reaction, while reducing interference from a competing fast neutron induced reaction on phosphorus in bone, <SUP>31</SUP>P(n,α)<SUP>28</SUP>Al. Initially the MCNP code was benchmarked against an existing fast neutron activation analysis (FNAA) system at Singleton Hospital, Swansea. The MCNP calculations were found to be accurate within inherent statistical limits (≤ 3%). Modifications of the FNAA system were then investigated using MCNP. This study indicated that due to high levels of interference from a fast neutron reaction on phosphorus the system was unlikely to be able to measure Al with acceptable sensitivity. Finally a completely new design of a TNAA system was developed using MCNP. The design was based on a cylindrical D<SUB>2</SUB>O moderator with the <SUP>252</SUP>Cf source positioned along the central axis of the cylinder and is designed to be sufficiently compact to be used in a clinical environment. Surrounding the moderator by a graphite reflector showed further improvement in the thermal-to-fast flux ratio. The dose equivalent delivered to a hand phantom in 20 minutes using a 1 mg source was 0.12 mSv. Results of the simulations indicate that the system could be made sufficiently sensitive to measure bone Al concentrations down to levels close to the normal range.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:638297 |
| Date | January 1995 |
| Creators | Natto, S. S. A. |
| Publisher | Swansea University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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