Effects of silicon photomultipliers with digital readout and the Bayesian penalizedlikelihood reconstruction algorithm on defining metabolic tumor volume in positron emission tomography: Phantom studies

Abstract

Abstract Objective The present study aimed to evaluate the influence of silicon photomultiplier positron emission tomography (SiPM-PET) and Bayesian penalized likelihood reconstruction (BPL) on metabolic tumor volume (MTV) by comparing the results with those from traditional photomultiplier tube PET (PMT-PET). Methods Six phantoms of varying shapes and volumes (1.2, 2.6, 5.6, 11.5, 15, and 20 mL) were created using a mixture of fluorodeoxyglucose-18 (18F) solution and agar at a background ratio of 1:4, and placed in a 5 L polytank. SiPM-PET and PMT-PET were each performed for five min. PMT-PET utilized traditional ordered subset expectation maximization (OSEM), while SiPM-PET utilized both OSEM and BPL for image reconstruction. MTV calculations were performed using both the traditional relative threshold method (30, 40, 42, and 50% of maximum standardized uptake value [SUVmax]) and the gradient-based method (weight coefficients, 0.3, 0.4, 0.5, and 0.6), and the measurements obtained were compared with the actual volume of the phantoms to evaluate accuracy. Results SiPM-PET-based contour extraction more accurately reflected the shape of each phantom than PMT-PET alone. In terms of accuracy in calculating MTV, a relative threshold method of 40% and a weight coefficient of 0.4 yielded results that were closest to the actual volumes of the phantoms. When SiPM-PET was used with BPL, the MTV calculated using the gradient-based method most closely approximated the know phantom volume. Conclusion The use of BPL in conjunction with SiPM-PET imaging significantly improved spatial resolution, allowing for a clearer delineation of tumor boundaries. Consequently, the MTV calculations obtained using SiPM-PET with BPL were more accurate than those obtained using PMT-PET or SiPM-PET with OSEM, indicating its potential for more precise tumor volume measurement in oncologic PET imaging.