IMPROVING THE QUANTIFICATION ACCURACY OF Tc-99m MIBI DUAL-PHASE PARATHYROID SPECT/CT: A MONTE CARLO SIMULATION STUDY

Year 2023, , 9 - 23, 30.12.2023

Albert Güveniş , Bahadır Aytaç

https://doi.org/10.38061/idunas.1325839

Abstract

Objective: Quantitative parathyroid SPECT imaging is a technique used to assess Primary hyperparathyroidism that may have potential in the identification and differentiation of parathyroid lesions as well as the estimation of disease severity. Studying the effect of data acquisition parameters on the quantification error is important for maximizing the accuracy of this diagnostic technique. In this study we examine the effects of different data acquisition parameters, namely the type of collimator, scatter correction status and reconstruction iteration number on the quantification accuracy using computer simulation. Methods: The SIMIND Monte Carlo Simulation and CASToR iterative reconstruction program was used to simulate a commercially available SPECT camera (Siemens Symbia Intevo Gamma Camera) with a crystal size of 29.55cm and 128x128 matrix size. A digital cylindrical phantom filled with water was constructed. A 0.36 cm radius spherical adenoma filled with a uniform 1MBq radioactivity is placed within the phantom. Low-Energy High Resolution (LEHR) and Low Energy Ultra High Resolution (LEUHR) collimator models are tested. Along with the presence of Scatter correction and differing iteration numbers (x16, x32). An image FOV based calibration method was used to gather quantitative information and checked against the input radioactivity. Results: The presence of scatter correction caused a 15-20% relative improvement in quantification accuracy. The optimal number of iterations produced a 10% relative improvement. Overall, accuracies as good as 7% in estimated activity concentration could be observed. Conclusion: The optimization of parameters can provide a significant improvement in quantification accuracy.

Keywords

SPECT, Monte Carlo Simulation, Quantification, Hyperparathyroidsm

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