Evaluation of image resolution and quantification parameters on fdg-pet/ct images in patients with metastatic breast cancer using Q. clear and osem reconstruction techniques

Abstract

We compared the 2-[18F]FDG-PET/CT scans performed for response monitoring in patients with metastatic breast cancer in a prospective setting using the ordered subset expectation maximization (OSEM) algorithm and the bayesian penalized likelihood reconstruction algorithm (Q.Clear) and the image quality and quantification parameters. 35 patients with metastatic breast cancer who were treated and followed up with 2-[18F]FDG-PET/CT were included. A total of 150 scans were evaluated on a five-point scale for the image quality parameters of noise, sharpness, contrast, diagnostic confidence, artefact, and blotchy look while being blinded to the Q.Clear and OSEM reconstruction algorithms. In scans with detectable disease, the lesion with the highest volume of interest was chosen, taking into account both reconstruction techniques' interest levels. For the same heated lesion, SULpeak (g/mL) and SUVmax (g/mL) were contrasted. The OSEM reconstruction had significantly less blotchy appearance than the Q.Clear reconstruction, while there was no significant difference between the two methods in terms of noise, diagnostic confidence, or artefact. Q.Clear had significantly better sharpness (p < 0.002) and contrast (p < 0.002) than the OSEM reconstruction. Quantitative examination of 75/150 scans revealed that Q.Clear reconstruction considerably outperformed OSEM reconstruction in terms of SULpeak (6.33 ± 1.8 vs. 5.85 ± 1.5, p < 0.002) and SUVmax (7.27 ± 5.8 vs. 3.90 ± 2.8, p 0.002). In conclusion, OSEM reconstruction was less blotchy, but Q.Clear reconstruction showed superior sharpness, better contrast, higher SUVmax, and higher SULpeak.