BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients.
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 s...
| Publicado en: | Journal of Digital Imaging Vol. 35; no. 3; pp. 581 - 594 |
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| Autores principales: | , , , , , , , , , , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=157184672&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157184672 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2022 vid: 35 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 157184672 155425910 157184672 157184672 10.1007/s10278-021-00570-y 157184672 ppf: 581 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients. aug: au: Liberini, Virginia Pizzuto, Daniele A. Messerli, Michael Orita, Erika Grünig, Hannes Maurer, Alexander Mader, Cäcilia Husmann, Lars Deandreis, Désirée Kotasidis, Fotis Trinckauf, Josey Curioni, Alessandra Opitz, Isabelle Winklhofer, Sebastian Huellner, Martin W. affil: Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, Zürich, Switzerland sug: subj: Brain Neoplasms Diagnosis Neoplasm Metastasis Diagnosis Fludeoxyglucose F 18 Positron-Emission Tomography Lung Neoplasms Cancer Patients Algorithms Human Retrospective Design Record Review Neoplasm Staging Magnetic Resonance Imaging Descriptive Statistics Friedman Test Quantitative Studies Comparative Studies kappa Statistic ab: 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. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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