Impact of the counts density of calibration image and the image reconstruction parameters in 131I SPECT image quantification

Abstract

131 I) has been used for diagnosis and therapy in Nuclear Medicine Centers in Brazil for more than 50 years.The present study aims to investigate the impact of the counts density and the reconstruction parameters in the calibration factor determination and in the image quantification, considering the reality of Brazilian dosimetry studies.For this task, images were quantified using calibration images with high and low counts density and reconstructed adopting two different parameters approaches, usually employed in patients images. SPECT quantification results presented in this work follow other previous 131 I SPECT studies and suggest that, due to the long time interval between the first e last images, as required by the Brazilian guideline, the image quantification accuracy can be improved if the counts density of calibration images is considered.

Improved system calibration for 131I SPECT image quantification

“…Differences between HCD and LCD calibration factors for each source position suggest that the accuracy of SPECT quantification can be improved if the count density of the image to be quantified is considered in the calibration procedure. In dosimetry studies, the count density varies considerably over imaging times [18,22].…”

Influence of the SPECT calibration source position on the absorbed dose calculation for 131I-NaI therapy using GATE simulations

“…Patient images from the HC/UNICAMP database were acquired eight to ten days after therapeutic dose administration with approximately 3000 counts per projection image, as required by the Brazilian guideline for thyroid therapy [5]. Based on this analysis, images of this study were acquired with 15 000 counts per projection for high counts density (HCD) and 3000 counts per projection for low counts density (LCD).…”

“…The ordered subsets expectation maximization (OSEM) iterative algorithm, provided by Syngo workstation, was used for the image reconstruction. The iterative image reconstruction also affects the image quantification results due to the impact of the image noise, which increases with the numbers of iterations, particularly in LCD acquisitions [5,22]. Hence, images with a higher number of counts can be reconstructed using more iterations and subsets, resulting in a faster and more accurate final image [22].…”

“…It is a multi-step procedure with uncertainty associated with each step [3]. Image quantification is the base for organ dosimetry studies since it is the only method for quantitative measurement of tracer uptake that determines residual activity in a specific anatomical region, evaluated in the image through a region of interest (ROI) or volume of interest (VOI) [4,5]. Therefore, it becomes essential to reduce possible sources of errors related to image quantification to achieve a suitable accuracy in internal dosimetry [6].…”

“…Furthermore, it suggests performing calibration using a source positioned at the center of a phantom filled with water to approximate the scatter and attenuation conditions in patient imaging [2]. The impacts of calibration source geometry [8,10], reconstruction parameters [5,11] and background radiation [6] at the system calibration were studied in previous works. However, the influence of calibration source position in dose calculation is an issue requiring investigation.…”