PT - JOURNAL ARTICLE AU - Pei Ing Ngam AU - Eelin Tan AU - Gabriel Lim AU - Sean Xuexian Yan TI - Improving Yittrium-90 PET scan image quality through optimized reconstruction algorithms AID - 10.2967/jnmt.122.264439 DP - 2022 Nov 01 TA - Journal of Nuclear Medicine Technology PG - jnmt.122.264439 4099 - http://tech.snmjournals.org/content/early/2022/11/09/jnmt.122.264439.short 4100 - http://tech.snmjournals.org/content/early/2022/11/09/jnmt.122.264439.full AB - The study aimed to improve the quality of the Y90 PET imaging by optimizing the reconstruction algorithm. Methods: Ten patients with metastatic neuroendocrine tumour to the liver or primary hepatocellular carcinoma who were qualified for Y90 labelled selective internal radiation therapy (SIRT) or peptide receptor radionuclide therapy (PRRT) were recruited. They underwent post-therapy PET/CT imaging using three different reconstruction parameters: (Algorithm A)Vue Point HD with 6.4mm filter cutoff, 24 subsets and 2 iterations, (Algorithm B)Vue Point FX with 6.0 mm filter cutoff, 18 subsets and 3 iterations using time of flight, and (Algorithm C)Vue Point HD LKYG with 5mm filter cutoff, 32 subsets and 1 iteration. The reconstructed PET/CT images were assessed by 10 nuclear medicine physicians using 4-point semi-qualitative scoring criteria. A P-value of less than 0.05 was considered significant. Results: The median quality assessment scores for Algorithm C were consistently scored the highest with algorithms A, B and C scoring 3, 2 and 4 respectively. The Y90 PET scans using Algorithm C were deemed diagnostic 91% of the time. There was a statistically significant difference in quality assessment scores between the algorithms by the Kruskal-Wallis rank sum test (χ2(2) = 86.5, P <0.001), with mean rank quality score (QS) of 130.03 for Algorithm A, 109.76 for Algorithm B and 211.71 for Algorithm C. Subgroup analysis for quality assessment score of post-PRRT imaging alone showed statistically significant difference between different scanning algorithms (χ2(2) = 35.35, P < 0.001), with mean rank QS of 45.85 for Algorithm A, 50.05 for Algorithm B and 85.6 for Algorithm C. Similar results were observed for quality assessment score of post-SIRT imaging (χ2(2) = 79.90, p<0.001), with mean rank of 82.33 for Algorithm A, 55.79 for Algorithm B and 133.38 for Algorithm C. Conclusion: The new LKYG algorithm that was featured by decreasing the number of iterations, decreasing the cutoff of the filter thickness, and increasing the number of the subsets had successfully improved the image quality.