Effect of Bayesian penalty likelihood algorithm on 18F-FDG PET/CT image of lymphoma

Optimizing scan time and bayesian penalized likelihood reconstruction algorithm in copper-64 PET/CT imaging: a phantom study

Objectives: The aim of this study was to evaluate Cu-64 PET phantom image quality using Bayesian Penalized Likelihood (BPL) and Ordered Subset Expectation Maximum with point-spread function modeling (OSEM-PSF) reconstruction algorithms. In the BPL, the regularization parameterβwas varied to identify the optimum value for image quality. In the OSEM-PSF, the effect of acquisition time was evaluated to assess the feasibility of shortened scan duration.Methods: A NEMA IEC PET body phantom was filled with known activities of water soluble Cu-64. The phantom was imaged on a PET/CT scanner and was reconstructed using BPL and OSEM-PSF algorithms. For the BPL reconstruction, variousβvalues (150, 250, 350, 450, and 550) were evaluated. For the OSEM-PSF algorithm, reconstructions were performed using list-mode data intervals ranging from 7.5 to 240 s. Image quality was assessed by evaluating the signal to noise ratio (SNR), contrast to noise ratio (CNR), and background variability (BV).Results: The SNR and CNR were higher in images reconstructed with BPL compared to OSEM-PSF. Both the SNR and CNR increased with increasingβ, peaking atβ= 550. The CNR for allβ, sphere sizes and tumor-to-background ratios (TBRs) satisfied the Rose criterion for image detectability (CNR > 5). BPL reconstructed images withβ= 550 demonstrated the highest improvement in image quality. For OSEM-PSF reconstructed images with list-mode data duration ≥ 120 s, the noise level and CNR were not significantly different from the baseline 240 s list-mode data duration.Conclusions: BPL reconstruction improved Cu-64 PET phantom image quality by increasing SNR and CNR relative to OSEM-PSF reconstruction. Additionally, this study demonstrated scan time can be reduced from 240 to 120 s when using OSEM-PSF reconstruction while maintaining similar image quality. This study provides baseline data that may guide future studies aimed to improve clinical Cu-64 imaging.

The variation of quantitative parameters and Deauville scores with different reconstruction algorithms in FDG PET/CT imaging of lymphoma patients

INTRODUCTION AND OBJECTIVES

18F-FDG PET with the Deauville score (DS) is a unique semiquantitative method for lymphoma. However, type of standard uptake values (max, mean, and peak) reconstruction algorithms could affect DS. We compared the Bayesian Penalized Likelihood reconstruction algorithm (BPL) with Ordered Subsets Expectation Maximization (OSEM) on quantitative parameters and DS in lymphoma. We investigated the effect of the size of the lymph node on quantitative variation.

PATIENTS AND METHODS

Raw PET data of 255 lymphoma patients were reconstructed separately with Q.Clear (GE Healthcare), a BPL, and SharpIR (GE Healthcare), an OSEM algorithm. In both images, each patient's liver, mediastinal blood pool, and SUVs (SUVmax, SUVmean, and SUVpeak) of a total of 487 lesions selected from the patients were performed. DSmax, DSmean, and DSpeak were compared.

RESULTS

In our study, DS increased significantly with BPL (p < 0.001), and the DS increased to 4-5 in thirty patients evaluated as 1-2-3 with OSEM. It was found that the quantitative values of the lymph nodes increased statistically with BPL (p < 0.001), and the liver from the reference regions were significantly decreased (p < 0.001). In addition, difference in lymph node was independently associated with size of lesion and was significantly more pronounced in small lesions (p < 0.001). The effects of BPL algorithm were more pronounced in SUVmax than in SUVmean and SUVpeak. DS-mean and DS-peak scores were less changed by BPL than DS-max.

CONCLUSION

Different reconstruction algorithms in FDG PET/CT affect the quantitative evaluation. That variation may affect the change in DS in lymphoma patients, thus affecting patient management.

Phantom and clinical evaluation of Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm in 68Ga-PSMA PET-CT studies

In this study, we aimed to examine the effect of varying β-values in the block sequential regularized expectation maximization (BSREM) algorithm under differing lesion sizes to determine an optimal penalty factor for clinical application. The National Electrical Manufacturers Association phantom and 15 prostate cancer patients were injected with 68Ga-PSMA and scanned using a GE Discovery IQ PET/CT scanner. Images were reconstructed using ordered subset expectation maximization (OSEM) and BSREM with different β-values. Then, the background variability (BV), contrast recovery, signal-to-noise ratio, and lung residual error were measured from the phantom data, and the signal-to-background ratio (SBR) and contrast from the clinical data. The increment of BV using a β-value of 100 was 120.0%, and the decrement of BV using a β-value of 1000 was 40.5% compared to OSEM. As β decreased from 1000 to 100, the [Formula: see text] increased by 59.0% for a sphere with a diameter of 10 mm and 26.4% for a sphere with a diameter of 37 mm. Conversely, [Formula: see text] increased by 140.5% and 29.0% in the smallest and largest spheres, respectively. Furthermore, the Δ[Formula: see text] and Δ[Formula: see text] were - 41.1% and - 36.7%, respectively. In the clinical study, OSEM exhibited the lowest SBR and contrast. When the β-value was reduced from 500 to 100, the SBR and contrast increased by 69.7% and 71.8% in small and 35.6% and 33.0%, respectively, in large lesions. Moreover, the optimal β-value decreased as lesion size decreased. In conclusion, a β-value of 400 is optimal for small lesion reconstruction, while β-values of 600 and 500 are optimal for large lesions in phantom and clinical studies, respectively.

The frequency of change in five-point scale score with a Bayesian penalised likelihood PET reconstruction algorithm on interim FDG PET-CT and its potential implications for therapy decisions in Hodgkin's lymphoma

AIM

To assess the effect of a Bayesian penalised likelihood (BPL) reconstruction algorithm on the five-point scale (5-PS) score, response categorisation, and potential implications for therapy decisions after interim 2-[¹⁸F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET)-computed tomography (CT) (iPET-CT) to guide treatment in classical Hodgkin's lymphoma (HL).

MATERIALS AND METHODS

The present study included new patients with HL undergoing iPET-CT from 2014-2019 after two cycles of doxorubicin (Adriamycin), bleomycin, vincristine, and dacarbazine (ABVD). Two reporters categorised response using the 5-PS and measured maximum standardised uptake values (SUV_max) of the most avid tumour residuum, mediastinal blood pool, and normal liver with ordered subset expected maximisation (OSEM) and BPL reconstructions.

RESULTS

Eighty-one iPET-CT examinations were reviewed. Compared with OSEM, BPL increased the 5-PS score by a single score in 18/81 (22.2%) patients. The frequency of potential treatment intensification by changing a score of 3-4 was 13.6% (11/81) and represented 25% (11/44) of patients with a score of 3 on OSEM. All 11 patients remained in remission without a change in therapy (mean 63 months) except one who required second-line treatment for refractory disease. Median SUV_max of tumour residuum was significantly higher with BPL compared with OSEM (2.7 versus 2.4, p<<0.0001), whilst liver SUV_max was significantly lower for both reporters (up to 6.6%, p<0.0001).

CONCLUSION

BPL PET reconstruction increased the 5-PS score on iPET-CT in 22% of HL patients and can potentially result in unnecessary treatment escalation in over half of these patients.