Paper
2 March 2006 The effect of detector resolution for quantitative analysis of neutron stimulated emission computed tomography
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Abstract
Previous research has shown benign and cancerous tissues to have different chemical make-ups. To measure the elemental concentration of biological samples noninvasively, we used neutron stimulated emission computed tomography (NSECT). When an incident neutron scatters inelastically from an atomic nucleus, it emits characteristic gamma energies, allowing for measurement of the elemental concentration of biological samples. Thus NSECT has the potential to be a method for precancerous tissue detection. In Monte Carlo simulations, we bombarded both a benign and a malignant human breast with 50 million neutrons. The resulting photon spectra were blurred to model the detector resolutions and then analyzed for peak detection. This simulation study analyzed the characteristic spectra using three detectors of different resolutions: a High-Purity Germanium (HPGe) semiconductor, a Bismuth Germanate (BGO) scintillator, and a Sodium Iodide (NaI) scintillator. The effective energy resolutions of these detectors are 0.1%, 7%, and 12%, respectively. The detectability of element peaks in the breast model was greatly reduced when the blur increased from just 0.1% to 7%. These initial experiments are valuable in choosing optimal detectors for peak detection in further NSECT studies and indicate that high-resolution detectors, such as HPGe, are required for using spectral peak analysis for breast cancer prediction.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Janelle E. Bender, Carey E. Floyd, Brian P. Harrawood, Anuj J. Kapadia, Amy C. Sharma, and Jonathan L. Jesneck "The effect of detector resolution for quantitative analysis of neutron stimulated emission computed tomography", Proc. SPIE 6142, Medical Imaging 2006: Physics of Medical Imaging, 61424Z (2 March 2006); https://doi.org/10.1117/12.652812
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Cited by 6 scholarly publications.
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KEYWORDS
Sensors

Breast

Tissues

Monte Carlo methods

Germanium

Tumor growth modeling

Computed tomography

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