A number of studies have consistently shown that MTV of PET/CT can provide valuable diagnostic and prognostic information for malignant tumors, and can be used to monitor disease progression and evaluate treatment response [3, 4]. In addition, PET/CT has been proved to be very important for defining the target volume of radiotherapy. The precise definition of MTV is essential for increasing the radiation dose of pancreatic cancer, gynecological tumor and rectal cancer, reducing the risk of organ exposure, and developing personalized in vitro radiotherapy plan [13, 14]. PET quantitative accuracy is affected not only by the hardware of equipment, but also by reconstruction algorithms. The BPL reconstruction method is the latest commercial PET/CT reconstruction algorithm which can be used in clinic. In novel PET/CT imaging systems, BPL is allowed to be applied simultaneously with TOF and PSF, results in significant improvements in signal-to-noise ratio, contrast and reconstruction resolution while keeping the edge unchanged and better quantitation accuracy compared with conventional reconstruction methods .
In this study, the actual volumes of NEMA phantom spheres were used as the reference, and the BPL reconstruction algorithm significantly improved the measurement accuracy of MTV compared with the non-BPL reconstruction algorithm. BPL significantly reduced the MTV measurement error when using the 42%SUVmax threshold delineation method (p = 0.009). Parvizin et al.  carried out a study on PET/CT quantitative parameters of 42 liver metastases (mean diameter of 25 mm, range of 6–86 mm). Using 40%SUVmax as the threshold, the MTVs of lesions decreased from 21.5 ml (1.5–143.4 ml) of OSEM to 16.3 ml (0.7–110.4 ml) of BPL (p < 0.001). According to Vallot D et al. , the MTV of 61.8% tumor lesions in BPL group was lower than that in OSEM group, but the difference was not significant (p = 0.069). This result is attributed to the full convergence of BPL reconstruction algorithm. Compared with conventional OSEM methods, BPL can reduce the noise and increase the number of iterations. By regularizing the relative difference between adjacent pixels of β parameter penalized, the image presents the optimal contrast and reconstruction resolution while maintaining the edge of the lesion, so as to ensure the accuracy of MTV. In addition, the accuracy of the 42%SUVmax threshold method mostly depends on the accuracy of SUVmax. Phantom and clinical case studies have confirmed the role of BPL algorithm in accurate quantification of SUVmax, and this improvement is mainly focused on small lesions . Results shown in Table 1 are consistent with their findings, which show that BPL can significantly reduce the MTV measurement errors of 13 mm and 10 mm spheres. At the same time, the role of BPL algorithm to keep the lesion edge unchanged also avoids the Gibbs artifact of small lesion edge given from PSF [18, 19]. Therefore, compared with the non-BPL algorithm, the BPL algorithm obtains higher reconstruction spatial resolution , reduces the impact of partial volume effect on small lesions, and improves the quantitative accuracy of MTV for small lesions.
The latest research of Texte E et al. also proposed that BPL reconstruction method can significantly reduce the MTV of lung tumor lesions, and results are also closely related to the delineation method of tumor lesions . In this study, the incremental% SUVmax threshold was used to find the optimal delineation threshold of the BPL and non-BPL methods. The results showed that the optimal segmentation threshold under BPL was fall in a relatively narrower range of 40% − 45%, when compared with the non-BPL group (45% − 60%). Notably, the segmentation threshold of small lesions needed to be adjusted to 60% to achieve acceptable MTV errors when using the non-BPL method. That is to say, under the BPL reconstruction method, the manufacturer's default setting of 42% can meet the acceptable MTV accuracy of any size lesions. This further avoids the error caused by manual adjustment of thresholds and increases the results repeatability.
The results also showed that, by using the BPL method, the MTV error range of the 42%SUVmax and the iterative adaptive methods are − 3.00% ~ 18.33% and − 3.22% ~ 15.00% (from 37 mm to 10 mm), respectively, and there was no significant difference between them (p = 0.699). It indicates that BPL algorithm can make the measurement less affected by the segmentation method. With the non-BPL reconstruction method, PET/CT quantitative studies on cervical cancer and lung cancer lesions have confirmed that the iterative adaptive method can improve the MTV measurement accuracy [10, 11]. The iterative adaptive method is to get the optimal threshold value by weighting SUVmax and SUVmean in the targeted lesion . This means that MTV measured by the iterative adaptive method is determined by SUVmax and SUVmean at the same time. This is more accurate than that of percentage SUVmax threshold method, which is only determined by SUVmax. Therefore, in view of the performance advantages of BPL reconstruction algorithm combined with iterative adaptive delineation methods the results of this study have guiding value for clinical practice of quantitative accuracy of PET/CT volumetric measures.
In this study, we did not study the effect of BPL on the accuracy of MTV measurement of actual tumor lesions. The research of NEMA phantom was carried out under the ideal conditions of regular shape and uniform radioactive distribution, the impact of BPL on MTV measurement accuracy of tumor lesions with irregular edge and heterogeneous radioactive uptake may be different. In addition, the sphere-to-background ratio was 4: 1 in this study, the results of different sphere-to-background ratios need to be further investigated by relevant phantom and clinical studies.