A Study on Determination of an Optimized Detector for Single Photon Emission Computed Tomography

Gamma radiation detector selection for CT scanner

Three types of gamma radiation detectors associated with distributed electronics namely, NaI (Tl), HPGe and LaBr3(Ce) are compared primarily focusing on electronic noise and scattering noise. Additionally, detectors of same make, material, size and electronics are also compared. A methodology is proposed to select the most suitable detector for computed tomography (CT) among the available options. Standard deviation parameter is employed to estimate electronic noise without performing CT experiment. Kanpur theorem-1(KT-1) is used to estimate the scattering noise quantitatively after verifying its sensitivity to scattering noise. The impact of scattering noise on CT profiles is evaluated using dice similarity dice coefficient. A good resemblance between KT-1 and dice coefficient is observed. A maximum difference of 56% in scattering noise is observed when five detectors used simultaneously instead of single detector whereas a discrepancy of 85% is observed between different types of radiation detectors. As far as ease of handling, operational and capital cost is concern one has to compromise minimum 12% of accuracy in CT reconstruction if NaI (Tl) detector is used with respect to best alternative available. The proposed methodology can be applied to measurement that require minimal scattering interference data other than CT experiments. The manufacturer can add noise level of detector as a characteristic parameter in the data sheet.

Verification of phantom accuracy using a Monte Carlo simulation: bone scintigraphy chest phantom

We aimed to compare the measurement and simulation data of bone scintigraphy of a chest phantom using a Monte Carlo simulation to verify the accuracy of the simulated data. The SIM² bone phantom was enclosed using 300 kBq/mL of technetium-99 m (^99mTc) to represent the bone tumor and 50 kBq/mL of ^99mTc to represent normal bone. Projection data were obtained using single-photon emission computed tomography (SPECT). Simulated projection data were constructed based on CT data. The contrast ratio, recovery coefficient (RC), % coefficient variation (CV), and power spectrum density (PSD) of each part were calculated from the reconstructed data. The contrast ratio and RC were equal between the actual and simulated data. Higher % CV values were noted for soft tissue than for normal bone. The PSD was equal for all frequency band ranges. Our results prove the utility of the Monte Carlo simulation for verifying various data using phantoms.