Optimization of oncological <sup>18</sup>F‐FDG PET/CT imaging based on a multiparameter analysis

Menezes, Vinícius O.; Machado, Marcos; Queiroz, Cleiton; Souza, S.O.; D’Errico, Francesco; Namías, Mauro; Larocca, Ticiana Ferreira; Soares, Milena Botelho Pereira

doi:10.1118/1.4940354

Cited by 15 publications

(34 citation statements)

References 42 publications

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“…Variation could also be caused by possible (unknown) liver inhomogeneities within the VOI. Nevertheless, the clarified variability is slightly lower but comparable with findings by de Groot et al [20] and Menezes et al [21]. In both 18 F-FDG studies, body mass also has the highest R 2 with respectively SNRnorm (R 2 = 0.77, Biograph mCT with OSEM3D + PSF + TOF reconstruction) and the normalized coefficient of variation (R 2 = 0.86, Biograph trueV with OSEM3D + PSF reconstruction).…”

Section: Discussionsupporting

confidence: 85%

“…This study showed that a quadratic relationship between administered activity, body mass, and acquisition time delivered a more constant PET image quality than a linear dose regimen for 18 F-FDG. Moreover, in a later study by Menezes et al [21], body mass was found as best predictor in a univariate analysis. Furthermore, a multivariate analysis in a study by Wickham et al [12] showed a combination of body mass, sex, and length as best predictors.…”

Section: Introductionmentioning

confidence: 80%

“…The NECR method is proposed to be more objective [12,31,32], as the liver SNR method might also be affected by variation in liver metabolism and reconstruction parameters. Menezes et al [21] used also NECR data, and also found body mass as the parameter with the strongest correlation (R 2 = 0.72). Furthermore, using the NECR method, Wickham et al [12] developed a multivariate fit based on patient sex, height, and weight for the Biograph mCT.…”

Section: Discussionmentioning

confidence: 98%

“…3). A number of studies [12,19,21,31,32] used noise equivalent count rate (NECR) data as a measure of PET image quality. The NECR method is proposed to be more objective [12,31,32], as the liver SNR method might also be affected by variation in liver metabolism and reconstruction parameters.…”

Section: Discussionmentioning

confidence: 99%

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Standardized image quality for 68Ga-DOTA-TATE PET/CT

et al. 2020

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Background: Positron emission tomography (PET) imaging with 68 Gallium labeled somatostatin analogues (68 Ga-DOTA-SSA) plays a key role in neuroendocrine tumor management. The impact of patient size on PET image quality is not well known for PET imaging with 68 Ga-DOTA-SSA. The aim of this study is to propose a dose regimen based on patient size that optimizes image quality and yields sufficient image quality for diagnosis. Methods: Twenty-one patients (12 males, 9 females) were prospectively included for 68 Gallium-DOTA-Tyr3-Octreotate (68 Ga-DOTA-TATE) PET/CT, which was acquired in whole body list mode using 6 min per bed position (mbp). The list-mode events were randomly sampled to obtain 1 to 6 mbp PET reconstructions. For semiquantitative assessment of image quality, the signal-to-noise ratio (SNR) was measured in the liver. The SNR normalized (SNRnorm) for administered activity and mbp was correlated with body mass, length, body mass index, body mass/length, and lean body mass. Three experienced nuclear medicine physicians visually graded image quality using a 4-point scale, and categorically scored the number of somatostatin-receptor positive lesions for each reconstruction. To investigate the impact of image quality on lesion quantification, the mean, maximum, and peak standardized uptake values (SUVs) of one abdominal lesion were measured in the 1 to 6 mbp PET reconstructions. Results: Of all patient-dependent parameters, body mass showed the strongest correlation (R 2 = 0.6) with SNRnorm. Lesion detectability analysis showed no significant difference for 3-5 mbp compared with the complete 6 mbp PET reconstruction. The SUV measurements showed no significant (p > 0.05) differences across the reconstructions. Visual assessment revealed that an SNR of 6.2 results in PET scans with moderate to good image quality. A non-linear expression was derived to calculate the required (dose × acquisition time) product (DTP) for the chosen SNR level of 6.2 that would yield a more constant image quality. Conclusion: Body mass can be used to predict 68 Ga-DOTA-TATE PET image quality. The proposed non-linear dose regimen based on body mass standardizes the image quality while maintaining sufficient image quality for diagnosis.

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Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 80%

Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

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Standardized image quality for 68Ga-DOTA-TATE PET/CT

et al. 2020

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“…Despite the wide literature on optimization of PET protocols for lesion detectability (6)(7)(8)(9)15) or the impact of noise on quantitation (16)(17)(18)(19), there is still limited work optimizing low-dose PET as a quantitative biomarker using guidelines such as the EANM criteria (20,21). Advances in PET image reconstruction algorithms that incorporate PSF modeling have reduced noise and increased resolution, potentially allowing for reduced injected activity and thus lower radiation exposure to patients (15,(22)(23)(24)(25), opening new scenarios for cancer screening with PET (15,26,27).…”

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confidence: 99%

Protocols for Harmonized Quantification and Noise Reduction in Low-Dose Oncologic ¹⁸F-FDG PET/CT Imaging

Machado

Menezes

Namías

et al. 2018

J. Nucl. Med. Technol.

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Oncological F-FDG PET/CT acquisition and reconstruction protocols need to be optimized for both quantitative and detection tasks. To date, most studies have focused on either quantification or noise, leading to quantitative harmonization guidelines or appropriate noise levels. We developed and evaluated protocols that provide harmonized quantitation with optimal amount of noise as a function of acquisition parameters and body mass. Multiple image acquisitions ( = 17) of the IEC/NEMA PET image quality phantom were performed with variable counting statistics. Phantom images were reconstructed with OSEM3D and PSF reconstructions for harmonized CRCmax quantification. The lowest counting statistics that resulted in compliance with EANM recommendations for CRCmax and CRCmax variability were used as optimization metrics. Image noise in the liver of 48 typical oncological F-FDG PET/CT studies was analysed with OSEM3D and PSF harmonized reconstructions. 164 additionalF-FDG PET/CT reconstructed list mode images were also evaluated to derive analytical expressions that predict image quality and noise variability. Phantom to subject translational analysis was used to derive optimized acquisition and reconstruction protocols. For harmonized quantitation levels, PSF reconstructions yielded decreased noise and lower CRCmax variability compared with regular OSEM3D reconstructions, suggesting they could enable a decreased activity regimen for matched performance. A PSF reconstruction with 7mm post-filter can provide harmonized quantification performance and acceptable image noise levels with injected activity, duration, and mass settings of 260 MBq.s/kg acquisition parameter at scan time. Similarly, the OSEM3D with 5mm post filter can provide similar performance with 401 MBq.s/kg.

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Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization

Queiroz

Machado

Ximenes

et al. 2021

J Applied Clin Med Phys

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Purpose: Methodologies for optimization of SPECT image acquisition can be challenging due to imaging throughput, physiological bias, and patient comfort constraints. We evaluated a vendor-independent method for simulating lower count image acquisitions. Methods: We developed an algorithm that recombines the ECG-gated raw data into reduced counting acquisitions. We then tested the algorithm to simulate reduction of counting statistics from phantom SPECT image acquisition, which was synchronized with an ECG simulator. The datasets were reconstructed with a resolution recovery algorithm and the summed stress score (SSS) was assessed by three readers (two experts and one automatic). Results: The algorithm generated varying counting levels, simulating multiple examinations at the same time. The error between the expected and the simulated countings ranged from approximately 5% to 10% for the ungated simulations and 0% for the gated simulations. Conclusions: The vendor-independent algorithm successfully generated lower counting statistics datasets from single-gated SPECT raw data. This method can be readily implemented for optimal SPECT research aiming to lower the injected activity and/ or to shorten the acquisition time.

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Optimization of oncological ¹⁸F‐FDG PET/CT imaging based on a multiparameter analysis

Cited by 15 publications

References 42 publications

Standardized image quality for 68Ga-DOTA-TATE PET/CT

Standardized image quality for 68Ga-DOTA-TATE PET/CT

Protocols for Harmonized Quantification and Noise Reduction in Low-Dose Oncologic ¹⁸F-FDG PET/CT Imaging

Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization

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Optimization of oncological 18F‐FDG PET/CT imaging based on a multiparameter analysis

Cited by 15 publications

References 42 publications

Standardized image quality for 68Ga-DOTA-TATE PET/CT

Standardized image quality for 68Ga-DOTA-TATE PET/CT

Protocols for Harmonized Quantification and Noise Reduction in Low-Dose Oncologic 18F-FDG PET/CT Imaging

Technical note: Partitioning of gated single photon emission computed tomography raw data for protocols optimization

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Optimization of oncological ¹⁸F‐FDG PET/CT imaging based on a multiparameter analysis

Protocols for Harmonized Quantification and Noise Reduction in Low-Dose Oncologic ¹⁸F-FDG PET/CT Imaging