The Impact of Total Variation Regularized Expectation Maximization Reconstruction on 68Ga-DOTA-TATE PET/CT Images in Patients With Neuroendocrine Tumor.

Lin Liu,Shijie Xu,Hanxiang Liu,Yue Chen,Greta S P Mok,Shumao Zhang,Yi Tao

doi:10.3389/fmed.2022.845806

Abstract

ObjectiveThe aim of this study was to investigate the effects of the total variation regularized expectation maximization (TVREM) reconstruction on improving 68Ga-DOTA-TATE PET/CT images compared to the ordered subset expectation maximization (OSEM) reconstruction.MethodA total of 17 patients with neuroendocrine tumors who underwent clinical 68Ga-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 SUVmean of the liver, background variability (BV), signal-to-noise ratios (SNR), SUVmax 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).ResultsIn total, 63 lesions were analyzed in this study. The SUVmean of the liver did not differ significantly between TVREM and OSEM. The BV of all TVREM groups was lower than OSEM groups (all p < 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 (p = 0.010 and 0.006). The SNR, SUVmax and TBR were higher for all TVREM groups compared to OSEM groups (all p < 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).ConclusionTVREM could reduce image noise, improve the SNR, SUVmax and TBR of the lesions, and has the potential to preserves the image quality with shorter acquisition time.

Highlights

Neuroendocrine tumors (NETs) are a heterogeneous group of cancers derived from the diffuse neuroendocrine system
Neuroendocrine cells are distributed in every organ, the primary NET may occur in any part of the human body, and early diagnosis of NET is very important for treatment [1]
The mean values of Background variability (BV) in OSME_2 and OSEM_3 were 8.2 ± 1.9% and 7.2 ± 1.9%, the BV in Total variation regularized expectation maximization (TVREM) groups decreased with the increase of penalization factors and the BV of R221 group was considered comparable to OSEM_3

Summary

Introduction

Neuroendocrine tumors (NETs) are a heterogeneous group of cancers derived from the diffuse neuroendocrine system. The specificity and sensitivity of these methods to NET are not high. One of the characteristics of neuroendocrine tumors is the high expression of somatostatin receptors (SSTR) [2]. SSTR-expression tends to correlate inversely with tumor grade and differentiation, and the role of SRI is more limited in high grade and in poorly differentiated carcinomas [3]. There are 5 somatostatin receptors (SSTR 1-5) widely expressed in both normal tissues and tumors. SST2 and 5 are usually over-expressed [4, 5]. This expression enables imaging with high sensitivity using PET with radioactively labeled somatostatin analogs such as 68Ga-DOTA-TATE. PET with 68Ga-labeled somatostatin ligands is well-established as a tool for localizing the primary tumor in metastatic NET [6, 7]

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