A Phantom Based Comparison of Image Segmentation Algorithms for Adaptive Functional Volume Determination of the Thyroid Gland using SPECT

Background One of the most used treatments for hyperthyroidism, is therapy with radioactive iodine (131I), which is accumulated in the thyroid gland. To determine the activity of 131I to be administered for a certain absorbed dose, the volume of the gland is of great importance but the historically used methods for estimating the functional volume of the gland are based on large approximations. The use of SPECT images enables increased accuracy of functional volume determination. However, there is a need for more realistic phantom studies and improved image segmentation. Aim The aim of this thesis was to find a robust method for image segmentation of the thyroid gland that could adapt to various object sizes and contrasts. The aim was also to develop an accessible and flexible 3D thyroid phantom for measurements and optimisation of parameter settings. Materials and Methods Thyroid phantoms made from playdough loaded with 99mTcO4-, were placed in a neck phantom filled with 99mTcO4- solution of various concentration. SPECT and CT acquisitions of the phantoms were performed and the SPECT images were segmented using thresholding and region growing algorithms. The thresholds in the segmentation algorithms were optimised by minimisation of cost functions consisting of Dice score, against the CT-volume, and relative SPECT volume. To find thresholds that could be used on all phantom volumes and image backgrounds, two overall cost functions were optimised for high and low backgrounds respectively. The optimised thresholds were validated on another set of playdough phantoms. They were also used on a simpler plastic can phantom for comparison of the performance relative to the method used in the clinic today. Results The optimised thresholds showed a substantial divergence between the measurements, ranging from 40 to 58 % for the thresholding algorithm and from 8 to 19 % for the region growing algorithm. The overall optimised thresholds were 55 and 48 % for high and low image backgrounds for the thresholding algorithm which was selected for the validation measurements due to its lower overall cost function and high stability. The developed method indicated a higher accuracy in functional volume determination of the thyroid gland than the standard method used. Conclusions An image segmentation method for functional volume determination of the thyroid gland, that can adapt to image contrast, was developed in this thesis. The method indicates an improved accuracy for functional volume determination of thyroid glands, but more experiments would need to be conducted. The developed thyroid phantoms enable further optimisation of image segmentation parameters for various object sizes, contrasts and shapes. The results indicate that thresholds deduced from simpler phantoms may be too uncertain which might lead to overtreatment of hyperthyroidism with 131I. It was also indicated that thresholding is more suitable than region growing for image segmentation of SPECT images