The upper limit of the amount of x-rays that are scattered from a SPECT/CT room and are acquired by an adjacent
gamma camera is estimated using physical principles and approximations. Methods: We first estimated the amount of xrays
scattered from the patient to the ceiling of the SPECT/CT room, then the amount scattered from the ceiling through
the gap between the ceiling and the top of lead walls to reach outside of the room, and finally the amount acquired by an
adjacent gamma camera into the Tl-201 data. Results: The counts of scattered x-ray photons acquired in the Tl-201
energy window can reach 0.12% of the CT primary counts when the standard 2.13 m high lead walls are used for the
SPECT/CT room. Due to the high CT counts, contamination to the Tl-201 data cannot be ignored. It is not effective to
reduce the contamination by increase the lead height or change the floor plan because the scattered x-rays reduce
moderately with increasing lead height or different floor plans. When the lead height increases from 2.13 m to 2.74 m,
for example, the amount of scattered x-rays only decreases by 20%. With the same 2.13 m lead height, there is little
difference in the amount of scattered x-rays for three different floor plans. Conclusions: The standard lead walls for a
SPECT/CT room cannot prevent scattered x-rays from severe contamination to the Tl-201 data acquired by an adjacent
gamma camera. Since dramatic increase of lead height is costly and often prohibitive due to the heavy load, we
recommend that Tl-201 studies be stopped when an adjacent CT scanner is in operation.
KEYWORDS: Fourier transforms, Deconvolution, Sensors, Point spread functions, Photons, Spatial resolution, Cameras, Monte Carlo methods, Linear filtering, Algorithm development
The In-111 coincidence camera we previously proposed can significantly increase detection efficiency because collimators are no longer needed. However, the initial simulations indicated that spatial resolution was too poor for medical imaging. To improve the resolution, we derived an analytical deconvolution algorithm in this study. In the derivation, 1-D Fourier transform for the shift-invariant point spread function (PSF) with respect to the detector bin location t was carried out analytically. The Fourier transform is approximately a linear function of the source-to-detector distance s when s is greater than 5 cm and its variation over s is much slower than that of any extensive source. The Fourier transform of the PSF can thus be taken out of the integration over s with reasonable accuracy and its inversion is the deconvolution kernel. A low-pass filter was applied to the deconvolved Fourier transform to suppress high-frequency oscillation. Applying the derived deconvolution algorithm to computer simulated phantoms, we achieved a resolution of 2 cm for s = 10 cm. Compared to the pre-deconvolution resolution of 19 cm, this is a huge improvement but is still poor. The errors caused by the approximations made in the derivation can be further reduced and also the high-frequency behavior of the deconvolved Fourier transform can be improved using better deconvolution techniques. Monte Carlo simulations for more realistic sources with image noise should be performed for further evaluation.
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