Quantitative improvement of lymph nodes visualization of breast cancer using Tc-99m-nanocolloid SPECT/CT and updated reconstruction algorithm
Abstract
This study aimed to evaluate the impact of attenuation and scatter correction on the contrast to noise ratio values of SPECT and SPECT/CT images in sentinel lymph nodes scintigraphy. In addition, the effect of using an iterative reconstruction algorithm with variable iterations number and fixed subsets was also investigated. 35 patients with a total of 44 lymph nodes were recruited in the current study. SPECT/CT scans were performed 3-4 h following peri-tumoral Tc-99m-nanocolloid injection (approximate to 1 mCi) at four points. Two image types were generated including SPECT with attenuation and scatter correction (AC-SC) and SPECT without any correction (NoAC-NoSC). The acquired projections were repeatedly reconstructed with eight subsets and 10, 20, 30 and 40 iterations. Afterwards, the calculated contrast to noise ratio values were used to investigate the effect of number of iteration and to compare the image quality of SPECT/CT and SPECT only. The mean contrast to noise (CNR) values of SPECT/CT scans were found to be 19,737, 26,418, 34,282 and 31,187 at 10, 20, 30 and 40 iterations, respectively. Whereas, the mean CNR values in SPECT (NoAC-NoSC) were as low as 8506, 10,582, 13,791 and 12,143 at 10, 20, 30 and 40 iterations, respectively. The CNR values of both SPECT and SPECT/CT improved with increasing number of iterations up to 30 iterations and then slightly decreased after 30-40 iterations. Likewise, no significant difference was found between 10 and 20 iterations (P-value = 0.06) in SPECT/CT, while a statistically significant difference was observed between 10 iterations and both 30 and 40 iterations (P-value < 0.05). It is concluded that the attenuation and scatter correction in SPECT/CT optimized the CNR values up to threefold compared to SPECT alone. Thus, a considerable improvement in the CNR values and the image quality can be obtained by increasing the iterations number to peak of 30 iterations.
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