ArticleJournal of digital imaging2022
BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients.
Article in Journal of digital imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Reconstruction matters: influence of EARL standards and BSREM in [EJNMMI research · 2026Article
- Evaluation of regularization factor and attenuation correction method of Q.Clear reconstruction for brain PET/MR in epileptic patients.EJNMMI physics · 2026Article
- CoF-DResNet: Cancer Metastasis Recognition Network based on Dynamic Coordinated Metabolic Attention and Structural Attention.Current pharmaceutical biotechnology · 2025Article
- Review
- Long-term trends in total administered radiation dose from brain [European journal of nuclear medicine and molecular imaging · 2025Article
- [Frontiers in oncology · 2024Article
- Reduced count pediatric whole-bodyPediatric radiology · 2024Article
- Phantom and clinical evaluation of Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm in 68Ga-PSMA PET-CT studies.Physical and engineering sciences in medicine · 2023Article
- HYPR4D kernel method on TOF PET data with validations including image-derived input function.EJNMMI physics · 2022Article
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Authors and funding
15 authors at 3 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the study was to analyze the use of block sequential regularized expectation maximization (BSREM) with different β-values for the detection of brain metastases in digital fluorine-18 labeled 2-deoxy-2-fluoro-D-glucose (18F-FDG) PET/CT in lung cancer patients. We retrospectively analyzed staging/restaging 18F-FDG PET/CT scans of 40 consecutive lung cancer patients with new brain metastases, confirmed by MRI. PET images were reconstructed using BSREM (β-values of 100, 200, 300, 400, 500, 600, 700) and OSEM. Two independent blinded readers (R1 and R2) evaluated each reconstruction using a 4-point scale for general image quality, noise, and lesion detectability. SUVmax of metastases, brain background, target-to-background ratio (TBR), and contrast recovery (CR) ratio were recorded for each reconstruction. Among all reconstruction techniques, differences in qualitative parameters were analyzed using non-parametric Friedman test, while differences in quantitative parameters were compared using analysis of variances for repeated measures. Cohen's kappa (k) was used to measure inter-reader agreement. The overall detectability of brain metastases was highest for BSREM200 (R1: 2.83 ± 1.17; R2: 2.68 ± 1.32) and BSREM300 (R1: 2.78 ± 1.23; R2: 2.68 ± 1.36), followed by BSREM100, which had lower accuracy owing to noise. The highest median TBR was found for BSREM100 (R1: 2.19 ± 1.05; R2: 2.42 ± 1.08), followed by BSREM200 and BSREM300. Image quality ratings were significantly different among reconstructions (p < 0.001). The median quality score was higher for BSREM100-300, and both noise and metastases' SUVmax decreased with increasing β-value. Inter-reader agreement was particularly high for the detectability of photopenic metastases and blurring (all k > 0.65). BSREM200 and BSREM300 yielded the best results for the detection of brain metastases, surpassing both BSREM400 and OSEM, typically used in clinical practice.
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