Image Quality and Semiquantitative Measurements on the Biograph Vision PET/CT System: Initial Experiences and Comparison with the Biograph mCT

In May 2018, the Biograph Vision PET/CT system was installed at the University Medical Center Groningen. This study evaluated the initial experiences with this new PET/CT system in terms of perceived image quality and semiquantitative analysis in comparison to the Biograph mCT as a reference. Methods: In total, 20 oncologic patients were enrolled and received a single 3 MBq/kg injected dose of 18F-FDG followed by a dual-imaging PET scan. Ten patients were scanned on the Biograph mCT first, whereas the other 10 patients were scanned on the Biograph Vision first. The locally preferred clinically reconstructed images were blindly reviewed by 3 nuclear medicine physicians and scored (using a Likert scale of 1–5) on tumor lesion demarcation, overall image quality, and image noise. In addition, these clinically reconstructed images were used for semiquantitative analysis by measurement of SUVs in tumor lesions. Images acquired using reconstructions conform with the European Association of Nuclear Medicine Research Ltd. (EARL) specifications were also used for measurements of SUV in tumor lesions and healthy tissues for comparison between systems. Results: The 18F-FDG dose received by the 14 men and 6 women (age range, 36–84; mean ± SD, 61 ± 16 y) ranged from 145 to 405 MBq (mean ± SD, 268 ± 59.3). Images acquired on the Biograph Vision were scored significantly higher on tumor lesion demarcation, overall image quality, and image noise than images acquired on the Biograph mCT (P < 0.001). The overall interreader agreement showed a Fleiss κ of 0.61 (95% confidence interval, 0.53–0.70). Furthermore, the SUVs in tumor lesions and healthy tissues agreed well (within 95%) between PET/CT systems, particularly when EARL-compliant reconstructions were used on both systems. Conclusion: In this initial study, the Biograph Vision showed improved image quality compared with the Biograph mCT in terms of lesion demarcation, overall image quality, and visually assessed signal-to-noise ratio. The 2 systems are comparable in semiquantitatively assessed image biomarkers in both healthy tissues and tumor lesions. Improved quantitative performance may, however, be feasible using the clinically optimized reconstruction settings.

[1]  J. Uribe,et al.  Studies of a Next-Generation Silicon-Photomultiplier–Based Time-of-Flight PET/CT System , 2017, The Journal of Nuclear Medicine.

[2]  Ronald Boellaard,et al.  Quantitative oncology molecular analysis suite: ACCURATE , 2018 .

[3]  B. Hutton,et al.  Advances in clinical molecular imaging instrumentation , 2018, Clinical and Translational Imaging.

[4]  D. Townsend,et al.  Physical and clinical performance of the mCT time-of-flight PET/CT scanner , 2011, Physics in medicine and biology.

[5]  Thomas Beyer,et al.  Performance Evaluation of the Vereos PET/CT System According to the NEMA NU2-2012 Standard , 2018, The Journal of Nuclear Medicine.

[6]  J. S. Karp,et al.  Recent developments in time-of-flight PET , 2016, EJNMMI Physics.

[7]  Ronald Boellaard,et al.  Performance Characteristics of the Digital Biograph Vision PET/CT System , 2019, The Journal of Nuclear Medicine.

[8]  C. Melcher Scintillation crystals for PET. , 2000, Journal of Nuclear Medicine.

[9]  Thomas Beyer,et al.  Performance evaluation of the Biograph mCT Flow PET/CT system according to the NEMA NU2-2012 standard , 2015, EJNMMI Physics.

[10]  W. Oyen,et al.  Predictive and prognostic value of FDG‐PET in nonsmall‐cell lung cancer , 2007, Cancer.

[11]  Eric J. W. Visser,et al.  FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0 , 2014, European Journal of Nuclear Medicine and Molecular Imaging.

[12]  W. Moses Time of flight in PET revisited , 2003 .

[13]  Simon S. Martin,et al.  Dual-energy CT in patients with colorectal cancer: Improved assessment of hypoattenuating liver metastases using noise-optimized virtual monoenergetic imaging. , 2018, European journal of radiology.

[14]  Wolfgang A Weber,et al.  Monitoring response to treatment in patients utilizing PET. , 2005, Radiologic clinics of North America.

[15]  Christer Halldin,et al.  Advancement in PET quantification using 3D-OP-OSEM point spread function reconstruction with the HRRT , 2009, European Journal of Nuclear Medicine and Molecular Imaging.

[16]  Joos V Lebesque,et al.  Standardised FDG uptake: a prognostic factor for inoperable non-small cell lung cancer. , 2005, European journal of cancer.

[17]  B. Bendriem,et al.  Performance Characteristics of a New LSO PET/CT Scanner With Extended Axial Field-of-View and PSF Reconstruction , 2009, IEEE Transactions on Nuclear Science.

[18]  G. Davidzon,et al.  Initial experience with a SiPM-based PET/CT scanner: influence of acquisition time on image quality , 2018, EJNMMI Physics.

[19]  J. Bomanji,et al.  18F-FDG PET/CT Imaging In Oncology , 2011, Annals of Saudi medicine.

[20]  Guido Germano,et al.  Recent Advances and Future Progress in PET Instrumentation. , 2016, Seminars in nuclear medicine.

[21]  Hojong Choi,et al.  Instrumentation for Time-of-Flight Positron Emission Tomography , 2016, Nuclear Medicine and Molecular Imaging.

[22]  J. Karp,et al.  Performance of Philips Gemini TF PET/CT scanner with special consideration for its time-of-flight imaging capabilities. , 2007, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[23]  W Vaalburg,et al.  The value of FDG-PET in the detection, grading and response to therapy of soft tissue and bone sarcomas; a systematic review and meta-analysis. , 2004, Cancer treatment reviews.

[24]  Suleman Surti,et al.  Update on Time-of-Flight PET Imaging , 2015, The Journal of Nuclear Medicine.