The Impact of Total Variation Regularized Expectation Maximization Reconstruction on Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor
Overview
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Objective: The aim of this study was to investigate the effects of the total variation regularized expectation maximization (TVREM) reconstruction on improving Ga-DOTA-TATE PET/CT images compared to the ordered subset expectation maximization (OSEM) reconstruction.
Method: A total of 17 patients with neuroendocrine tumors who underwent clinical Ga-DOTA-TATE PET/CT were involved in this study retrospectively. The PET images were acquired with either 3 min-per-bed (min/bed) acquisition time and reconstructed with OSEM (2 iterations, 20 subsets, and a 3.2-mm Gaussian filter) and TVREM (seven penalization factors = 0.01, 0.07, 0.14, 0.21, 0.28, 0.35, and 0.42) for 2 and 3 min-per-bed (min/bed) acquisition time using list-mode. The SUV of the liver, background variability (BV), signal-to-noise ratios (SNR), SUV of the lesions and tumor-to-background ratios (TBR) were measured. The mean percentage difference in the SNR and TBR between TVREM with difference penalization factors and OSEM was calculated. Qualitative image quality was evaluated by two experienced radiologists using a 5-point score scale (5-excellent, 1-poor).
Results: In total, 63 lesions were analyzed in this study. The SUV of the liver did not differ significantly between TVREM and OSEM. The BV of all TVREM groups was lower than OSEM groups (all < 0.05), and the BV of TVREM 2 min/bed group with penalization factor of 0.21 was considered comparable to OSEM 3 min/bed group ( = 0.010 and 0.006). The SNR, SUV and TBR were higher for all TVREM groups compared to OSEM groups (all < 0.05). The mean percentage difference in the SNR and TBR was larger for small lesions (<10 mm) than that for medium (≥10 mm but < 20 mm) and large lesions (≥20 mm). The highest image quality score was given to TVREM 2 min/bed group with penalization factor of 0.21 (3.77 ± 0.26) and TVREM 3 min/bed group with penalization factor of 0.35 (3.77 ± 0.26).
Conclusion: TVREM could reduce image noise, improve the SNR, SUV and TBR of the lesions, and has the potential to preserves the image quality with shorter acquisition time.
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