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ISSN (Print): 1874-4710
ISSN (Online): 1874-4729

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Research Article

Clinical Application of a High Sensitivity BGO PET/CT Scanner: Effects of Acquisition Protocols and Reconstruction Parameters on Lesions Quantification

Author(s): Elena De Ponti, Cinzia Crivellaro, Sabrina Morzenti, Lavinia Monaco*, Sergio Todde, Claudio Landoni, Federica Elisei, Monica Musarra and Luca Guerra

Volume 15, Issue 3, 2022

Published on: 29 April, 2022

Page: [218 - 227] Pages: 10

DOI: 10.2174/1874471015666220107100200

Price: $65

Abstract

Aims: The aim of this retrospective study was to investigate SUVs variability with respect to lesion size, administered dose, and reconstruction algorithm.

Background: SUVmax and SUVpeak are influenced by technical factors as count statistics and reconstruction algorithms.

Objective: To fulfill the aim, we evaluated the SUVs variability with respect to lesion size, administered dose, and reconstruction algorithm (ordered - subset expectation maximization plus point spread function option - OSEM+PSF, regularized Bayesian Penalized Likelihood - BPL) in a 5 - rings BGO PET/CT scanner.

Methods: Discovery IQ scanner (GE Healthcare, Milwaukee, Wisconsin, US) was used for list mode acquisition of 25 FDG patients, 12 injected with 3.7 MBq/kg (Standard Dose protocol - SD) and 13 injected with 1.8 MBq/kg (Low Dose protocol - LD). Each acquisition was reconstructed at different time/FOV with both OSEM+PSF algorithm and BPL using seven different beta factors. SUVs were calculated in 70 lesions and analysed in function of time/FOV and Beta. Image quality was evaluated as a coefficient of variation of the liver (CV - liver).

Results: SUVs were not considerably affected by time/FOV. However, SUVs were influenced by beta: differences were higher in small lesions (37% for SUVmax, 15% for SUVpeak) compared to larger ones (14% and 6%). CV - liver ranged from 6% with Beta-500 (LD and SD) to 13% with Beta- 200 (LD). CV - liver of BPL with Beta-350 (optimized for clinical practice in our institution) in LD was lower than CV - liver of OSEM+PSF in SD.

Conclusion: When a high sensitivity 5 - rings BGO PET/CT scanner is used with the same reconstruction algorithm, quantification by means of SUVmax and SUVpeak is a robust standard compared to the activity and scan duration. However, both SUVs and image quality are influenced by reconstruction algorithms and the related parameters should be considered to obtain the best compromise between detectability, quantification, and noise.

Keywords: Lesion detectability, quantification, standard osem algorithm plus PSF option, regularized reconstruction algorithm, lesion, beta factor.

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[1]
Boellaard, R.; Delgado-Bolton, R.; Oyen, W.J.; Giammarile, F.; Tatsch, K.; Eschner, W.; Verzijlbergen, F.J.; Barrington, S.F.; Pike, L.C.; Weber, W.A.; Stroobants, S.; Delbeke, D.; Donohoe, K.J.; Holbrook, S.; Graham, M.M.; Testanera, G.; Hoekstra, O.S.; Zijlstra, J.; Visser, E.; Hoekstra, C.J.; Pruim, J.; Willemsen, A.; Arends, B.; Kotzerke, J.; Bockisch, A.; Beyer, T.; Chiti, A.; Krause, B.J. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur. J. Nucl. Med. Mol. Imaging, 2015, 42(2), 328-354.
[http://dx.doi.org/10.1007/s00259-014-2961-x] [PMID: 25452219]
[2]
Adams, M.C.; Turkington, T.G.; Wilson, J.M.; Wong, T.Z. A systematic review of the factors affecting accuracy of SUV measurements. AJR Am. J. Roentgenol., 2010, 195(2), 310-320.
[http://dx.doi.org/10.2214/AJR.10.4923] [PMID: 20651185]
[3]
Reynés-Llompart, G.; Gámez-Cenzano, C.; Romero-Zayas, I.; Rodríguez-Bel, L.; Vercher-Conejero, J.L.; Martí-Climent, J.M. Performance characteristics of the whole-body discovery IQ PET/CT system. J. Nucl. Med., 2017, 58(7), 1155-1161.
[http://dx.doi.org/10.2967/jnumed.116.185561] [PMID: 28302761]
[4]
De Bernardi, E.; Fallanca, F.; Gianolli, L.; Gilardi, M.C.; Bettinardi, V. Reconstruction of uptake patterns in PET: The influence of regularizing prior. Med. Phys., 2017, 44(5), 1823-1836.
[http://dx.doi.org/10.1002/mp.12205] [PMID: 28294341]
[5]
Teoh, E.J.; McGowan, D.R.; Macpherson, R.E.; Bradley, K.M.; Gleeson, F.V. Phantom and clinical evaluation of the bayesian penalized likelihood reconstruction algorithm Q.clear on an LYSO PET/CT System. J. Nucl. Med., 2015, 56(9), 1447-1452.
[http://dx.doi.org/10.2967/jnumed.115.159301] [PMID: 26159585]
[6]
GE Healthcare White Paper, Q.Clear. 2014. Available from: http://www3.gehealthcare.co.uk/~/media/documents/us-global/products/pet-ct/whitepaper/q%20clear/ge-healthcare-white-paper_qclear.pdf
[7]
Nuyts, J.; Becque, D.; Dupont, P.; Mortelmans, L. A concave prior penalizing relative differences for maximum-a-posteriori reconstruction in emission tomography. IEEE Trans. Nucl. Sci., 2002, 49(1), 56-60.
[http://dx.doi.org/10.1109/TNS.2002.998681]
[8]
Asma, E.; Ahn, S.; Ross, S.; Chen, A.; Manjeshwar, R. Accurate and consistent lesion quantitation with clinically acceptable penalized likelihood images. IEEE Nuclear Science Symposium Conference Record, 2012.
[http://dx.doi.org/10.1109/NSSMIC.2012.6551928]
[9]
Ahn, S.; Fessler, J.A. Globally convergent image reconstruction for emission tomography using relaxed ordered subsets algorithms. IEEE Trans. Med. Imaging, 2003, 22(5), 613-626.
[http://dx.doi.org/10.1109/TMI.2003.812251] [PMID: 12846430]
[10]
Jaskowiak, C.J.; Bianco, J.A.; Perlman, S.B.; Fine, J.P. Influence of reconstruction iterations on 18F-FDG PET/CT standardized uptake values. J. Nucl. Med., 2005, 46(3), 424-428.
[PMID: 15750154]
[11]
Ahn, S.; Ross, S.G.; Asma, E.; Miao, J.; Jin, X.; Cheng, L.; Wollenweber, S.D.; Manjeshwar, R.M. Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET. Phys. Med. Biol., 2015, 60(15), 5733-5751.
[http://dx.doi.org/10.1088/0031-9155/60/15/5733] [PMID: 26158503]
[12]
Taniguchi, T.; Akamatsu, G.; Kasahara, Y.; Mitsumoto, K.; Baba, S.; Tsutsui, Y.; Himuro, K.; Mikasa, S.; Kidera, D.; Sasaki, M. Improvement in PET/CT image quality in overweight patients with PSF and TOF. Ann. Nucl. Med., 2015, 29(1), 71-77.
[http://dx.doi.org/10.1007/s12149-014-0912-z] [PMID: 25258046]
[13]
Akamatsu, G.; Mitsumoto, K.; Ishikawa, K.; Taniguchi, T.; Ohya, N.; Baba, S.; Abe, K.; Sasaki, M. Benefits of point-spread function and time of flight for PET/CT image quality in relation to the body mass index and injected dose. Clin. Nucl. Med., 2013, 38(6), 407-412.
[http://dx.doi.org/10.1097/RLU.0b013e31828da3bd] [PMID: 23603585]
[14]
Wampl, S.; Rausch, I.; Traub-Weidinger, T.; Beyer, T.; Gröschl, M.; Cal-González, J. Quantification accuracy of neuro-oncology PET data as a function of emission scan duration in PET/MR compared to PET/CT. Eur. J. Radiol., 2017, 95, 257-264.
[http://dx.doi.org/10.1016/j.ejrad.2017.08.024] [PMID: 28987677]
[15]
Zeimpekis, K.G.; Barbosa, F.; Hüllner, M.; ter Voert, E.; Davison, H.; Veit-Haibach, P.; Delso, G. Clinical evaluation of PET image quality as a function of acquisition time in a new TOF-PET/MRI compared to TOF-PET/CT-initial results. Mol. Imaging Biol., 2015, 17(5), 735-744.
[http://dx.doi.org/10.1007/s11307-015-0845-5] [PMID: 25840683]
[16]
Wahl, R.L.; Jacene, H.; Kasamon, Y.; Lodge, M.A. From RECIST to PERCIST: Evolving Considerations for PET response criteria in solid tumors. J. Nucl. Med., 2009, 50(Suppl. 1), 122S-150S.
[http://dx.doi.org/10.2967/jnumed.108.057307] [PMID: 19403881]
[17]
Lasnon, C.; Quak, E.; Le Roux, P.Y.; Robin, P.; Hofman, M.S.; Bourhis, D.; Callahan, J.; Binns, D.S.; Desmonts, C.; Salaun, P.Y.; Hicks, R.J.; Aide, N. EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program. EJNMMI Phys., 2017, 4(1), 17.
[http://dx.doi.org/10.1186/s40658-017-0185-4] [PMID: 28560574]
[18]
Young, H.; Baum, R.; Cremerius, U.; Herholz, K.; Hoekstra, O.; Lammertsma, A.A.; Pruim, J.; Price, P. Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. Eur. J. Cancer, 1999, 35(13), 1773-1782.
[http://dx.doi.org/10.1016/S0959-8049(99)00229-4] [PMID: 10673991]
[19]
Boellaard, R. Mutatis mutandis: harmonize the standard! J. Nucl. Med., 2012, 53(1), 1-3.
[http://dx.doi.org/10.2967/jnumed.111.094763] [PMID: 22159159]
[20]
Dolci, C.; Spadavecchia, C.; Crivellaro, C.; De Ponti, E.; Todde, S.; Morzenti, S.; Turolla, E.A.; Crespi, A.; Guerra, L.; Landoni, C. Treatment response assessment in [18F]FDG-PET/CT oncology scans: Impact of count statistics variation and reconstruction protocol. Phys. Med., 2019, 57, 177-182.
[http://dx.doi.org/10.1016/j.ejmp.2018.12.038] [PMID: 30738523]
[21]
Chilcott, A.K.; Bradley, K.M.; McGowan, D.R. Effect of a bayesian penalized likelihood PET reconstruction compared with ordered subset expectation maximization on clinical image quality over a wide range of patient weights. AJR Am. J. Roentgenol., 2018, 210(1), 153-157.
[http://dx.doi.org/10.2214/AJR.17.18060] [PMID: 29091008]
[22]
Teoh, E.J.; McGowan, D.R.; Bradley, K.M.; Belcher, E.; Black, E.; Gleeson, F.V. Novel penalised likelihood reconstruction of PET in the assessment of histologically verified small pulmonary nodules. Eur. Radiol., 2016, 26(2), 576-584.
[http://dx.doi.org/10.1007/s00330-015-3832-y] [PMID: 25991490]
[23]
Teoh, E.J.; McGowan, D.R.; Bradley, K.M.; Belcher, E.; Black, E.; Moore, A.; Sykes, A.; Gleeson, F.V. 18F-FDG PET/CT assessment of histopathologically confirmed mediastinal lymph nodes in non-small cell lung cancer using a penalised likelihood reconstruction. Eur. Radiol., 2016, 26(11), 4098-4106.
[http://dx.doi.org/10.1007/s00330-016-4253-2] [PMID: 26914696]
[24]
Howard, B.A.; Morgan, R.; Thorpe, M.P.; Turkington, T.G.; Oldan, J.; James, O.G.; Borges-Neto, S. Comparison of Bayesian penalized likelihood reconstruction versus OS-EM for characterization of small pulmonary nodules in oncologic PET/CT. Ann. Nucl. Med., 2017, 31(8), 623-628.
[http://dx.doi.org/10.1007/s12149-017-1192-1] [PMID: 28689358]
[25]
Sampaio Vieira, T.; Borges Faria, D.; Azevedo Silva, F.; Pimentel, F.; Pereira de Oliveira, J. The impact of a Bayesian penalized likelihood reconstruction algorithm on the evaluation of indeterminate pulmonary nodules by dual-time point 18F-FDG PET/CT. Clin. Nucl. Med., 2017, 42(7), e352-e354.
[http://dx.doi.org/10.1097/RLU.0000000000001713] [PMID: 28525459]
[26]
Hsu, D.F.C.; Ilan, E.; Peterson, W.T.; Uribe, J.; Lubberink, M.; Levin, C.S. Studies of a next-generation silicon-photomultiplier-based time-of-flight PET/CT system. J. Nucl. Med., 2017, 58(9), 1511-1518.
[http://dx.doi.org/10.2967/jnumed.117.189514] [PMID: 28450566]

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