Miwa Kenta, Yamagishi Shin, Kamitaki Shun, Anraku Kouichi, Sato Shun, Yamao Tensho, Miyaji Noriaki, Wachi Kaito, Akiya Naochika, Wagatsuma Kei, Oguchi Kazuhiro
Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, 10-6 Sakaemachi, Fukushima-Shi, Fukushima, 960-8516, Japan.
Center of Radiology and Diagnostic Imaging, Aizawa Hospital, 2-5-1 Honjo, Matsumoto-Shi, Nagano, 390-8510, Japan.
EJNMMI Phys. 2025 Mar 28;12(1):29. doi: 10.1186/s40658-025-00742-7.
The digital-BGO PET/CT system, Omni Legend 32, incorporates modified block sequential regularized expectation maximization (BSREM) image reconstruction and a deep learning-based time-of-flight (TOF)-like image quality enhancement process called Precision DL (PDL). The present study aimed to define the fundamental characteristics of PDL using phantom and clinical images.
A NEMA IEC body phantom was scanned using the Omni Legend 32 PET/CT system. All PET/CT images were acquired over 60 and 90 s per bed position, with a 384 × 384 matrix. Phantom images were reconstructed using OSEM + PSF and BSREM at β values of 100-1,000, combined with low (LPDL), medium (MPDL), and high (HPDL) PDL. We evaluated contrast recovery, background variability, and the contrast-to-noise ratio (CNR) of a 10 mm hot sphere. Thirty clinical whole-body F-FDG PET/CT examinations were included. Clinical images were reconstructed using OSEM + PSF and BSREM at β values of 200, 300, 400, 500, and 600, determined based on findings from the phantom study, combined with the three PDL models. Noise levels, mean SUV (SUV), and the signal-to-noise ratio (SNR) of the liver as well as signal-to-background ratios (SBR) and maximum SUV (SUV) of lesions were evaluated. Two blinded readers evaluated visual image quality and rated several aspects to complement the analysis.
Contrast recovery and background variability decreased as the β value increased. This trend was consistent even when PDL processing was added to BSREM. Increased strength of the PDL models led to higher CNR. Noise levels decreased as a function of increasing β values in BSREM, resulting in a higher SNR, but lower SBR. Combining PDL with BSREM resulted in all β values producing better results in terms of noise, SBR, and SNR than OSEM + PSF. As the PDL increased (LPDL < MPDL < HPDL), noise levels, SBR, and SNR became higher. The β values of 400, 200, 300, and 300 for BSREM, LPDL, MPDL, and HPDL, respectively, resulted in noise equivalent to OSEM + PSF but significantly increased the SUV (9%, 15%, 18%, and 27%), SBR (16%, 17%, 20%, and 32%), and SNR (17%, 19%, 31%, and 36%), respectively. The visual evaluation of image quality yielded similar scores across BSREM + PDL reconstructions, although BSREM with β = 600 combined with MPDL delivered the best overall image quality and total mean score.
The combination of BSREM and PDL significantly enhanced the SUV of lesions and image quality compared with OSEM + PSF. A combination of BSREM at β values of 500-600 and MPDL is recommended for oncological whole-body PET/CT imaging when using PDL on the Omni Legend.
数字BGO正电子发射断层显像/计算机断层扫描（PET/CT）系统Omni Legend 32采用了改进的块序贯正则期望最大化（BSREM）图像重建技术以及一种基于深度学习的类似飞行时间（TOF）的图像质量增强程序，称为Precision DL（PDL）。本研究旨在利用体模和临床图像确定PDL的基本特征。
使用Omni Legend 32 PET/CT系统对NEMA IEC体模进行扫描。所有PET/CT图像在每个床位上采集60秒和90秒，矩阵大小为384×384。体模图像采用有序子集期望最大化（OSEM）+点扩散函数（PSF）以及β值为100 - 1000的BSREM进行重建，并结合低（LPDL）、中（MPDL）和高（HPDL）三种PDL模式。我们评估了10毫米热球的对比度恢复、背景变异性以及对比度噪声比（CNR）。纳入了30例临床全身F-FDG PET/CT检查。临床图像采用OSEM + PSF以及根据体模研究结果确定的β值为200、300、400、500和600的BSREM进行重建，并结合三种PDL模型。评估了肝脏的噪声水平、平均标准摄取值（SUV）、信噪比（SNR）以及病变的信号背景比（SBR）和最大SUV（SUV）。两名盲法阅片者评估视觉图像质量并对几个方面进行评分以补充分析。
随着β值增加，对比度恢复和背景变异性降低。即使在BSREM中加入PDL处理，这一趋势仍然一致。PDL模型强度增加导致CNR升高。在BSREM中，噪声水平随着β值增加而降低，从而使SNR升高，但SBR降低。将PDL与BSREM相结合使得所有β值在噪声、SBR和SNR方面都比OSEM + PSF产生更好的结果。随着PDL增加（LPDL < MPDL < HPDL），噪声水平、SBR和SNR升高。BSREM、LPDL、MPDL和HPDL的β值分别为400、200、300和300时，产生的噪声与OSEM + PSF相当，但SUV分别显著增加（9%、15%、18%和27%）、SBR分别显著增加（分别为16%、17%、20%和32%）、SNR分别显著增加（分别为17%、19%、31%和36%）。尽管β = 600结合MPDL的BSREM提供了最佳的整体图像质量和总平均分，但在BSREM + PDL重建中，图像质量的视觉评估得分相似。
与OSEM + PSF相比，BSREM和PDL的组合显著提高了病变的SUV和图像质量。在Omni Legend上使用PDL进行肿瘤全身PET/CT成像时，建议将β值为500 - 600的BSREM与MPDL相结合。
