4.7 Article

Phantom and Clinical Evaluation of the Bayesian Penalized Likelihood Reconstruction Algorithm Q.Clear on an LYSO PET/CT System

Journal

JOURNAL OF NUCLEAR MEDICINE
Volume 56, Issue 9, Pages 1447-1452

Publisher

SOC NUCLEAR MEDICINE INC
DOI: 10.2967/jnumed.115.159301

Keywords

positron emission tomography; image reconstruction; Bayesian penalized likelihood; NEMA; image quality; optimization

Funding

  1. National Institutes of Health Research (NIHR) [NIHR-HCS-D12-03-13] Funding Source: National Institutes of Health Research (NIHR)
  2. Cancer Research UK [16466] Funding Source: researchfish
  3. National Institute for Health Research [NIHR-HCS-D12-03-13] Funding Source: researchfish
  4. Department of Health [NIHR-HCS-D12-03-13] Funding Source: Medline

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Q.Clear, a Bayesian penalized-likelihood reconstruction algorithm for PET, was recently introduced by GE Healthcare on their PET scanners to improve clinical image quality and quantification. In this work, we determined the optimum penalization factor (beta) for clinical use of Q.Clear and compared Q.Clear with standard PET reconstructions. Methods: A National Electrical Manufacturers Association image-quality phantom was scanned on a time-of-flight PET/CT scanner and reconstructed using ordered-subset expectation maximization (OSEM), OSEM with point-spread function (PSF) modeling, and the Q.Clear algorithm (which also includes PSF modeling). Q.Clear was investigated for beta (B) values of 100-1,000. Contrast recovery (CR) and background variability (BV) were measured from 3 repeated scans, reconstructed with the different algorithms. Fifteen oncology body F-18-FDG PET/CT scans were reconstructed using OSEM, OSEM PSF, and Q.Clear using B values of 200, 300, 400, and 500. These were visually analyzed by 2 scorers and scored by rank against a panel of parameters (overall image quality; background liver, mediastinum, and marrow image quality; noise level; and lesion detectability). Results: As beta is increased, the CR and BV decreases; Q.Clear generally gives a higher CR and lower BV than OSEM. For the smallest sphere reconstructed with Q.Clear B400, CR is 28.4% and BV 4.2%, with corresponding values for OSEM of 24.7% and 5.0%. For the largest hot sphere, Q.Clear B400 yields a CR of 75.2% and a BV of 3.8%, with corresponding values for OSEM of 64.4% and 4.0%. Scorer 1 and 2 ranked B400 as the preferred reconstruction in 13 of 15 (87%) and 10 of 15 (73%) cases. The least preferred reconstruction was OSEM PSF in all cases. In most cases, lesion detectability was highest ranked for B200, in 9 of 15 (67%) and 10 of 15 (73%), with OSEM PSF ranked lowest. Poor lesion detectability on OSEM PSF was seen in cases of mildly F-18-FDG-avid mediastinal nodes in lung cancer and small liver metastases due to background noise. Conversely, OSEM PSF was ranked second highest for lesion detectability in most pulmonary nodule evaluation cases. The combined scores confirmed B400 to be the preferred reconstruction. Conclusion: Our phantom measurement results demonstrate improved CR and reduced BV when using Q.Clear instead of OSEM. A beta value of 400 is recommended for oncology body PET/CT using Q.Clear.

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