SynthesisJournal of neuro-oncology2016
The detectability of brain metastases using contrast-enhanced spin-echo or gradient-echo images: a systematic review and meta-analysis.
Synthesis in Journal of neuro-oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
44 citing papers in PubMed, 2 syntheses or guidelines pooled it, 67 citations in OpenAlex.
- Brain metastases: A Society for Neuro-Oncology (SNO) consensus review on current management and future directions.Neuro-oncology · 2022Guideline
- CT in the prediction of margin-negative resection in pancreatic cancer following neoadjuvant treatment: a systematic review and meta-analysis.European radiology · 2021Pooled it
- Influence of metastases composition on the conspicuity of melanoma brain metastases: a comparative study of post-contrast 3D T1WI GRE versus 3D T1WI TSE black blood.La Radiologia medica · 2026Article
- Artificial intelligence-amplified contrast enhancement in brain magnetic resonance imaging for improving image quality and lesion visualization: a prospective pilot study.Quantitative imaging in medicine and surgery · 2026Article
- Oncological value of MRI in brain metastasis: exploring the potential of combining post-contrast T1 TSE (SPACE) and T1 GRE (MPRAGE) for stereotactic radiosurgery planning and surveillance.Journal of neuro-oncology · 2025Article
- Prospective comparison of brain tumor detection and characterization using post-contrast Dixon uT1RESS and MPRAGE at 3 Tesla.European journal of radiology · 2025Article
- Evaluation of an abbreviated MRI protocol in the screening for brain metastases in the initial staging of lung cancer.Neuroradiology · 2025Article
- Gadopiclenol Versus Gadoterate Meglumine for Pediatric Brain MRI: An Intraindividual Comparison of Contrast Enhancement.AJR. American journal of roentgenology · 2025Article
- 3 Tesla stack-of-stars echo unbalanced T1 relaxation-enhanced steady-state MRI for brain tumor imaging: post-contrast comparison with MPRAGE.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Observational
- Improved detection of brain metastases using contrast-enhanced 3D black-blood TSE sequences compared to post-contrast 3D T1 GRE: a comparative study on 1.5-T MRI.European radiology · 2025Article
- Neuroimaging features of immune-related adverse events due to immune checkpoint inhibitor therapy.Insights into imaging · 2025Article
- Diagnostic Confidence of Contrast-Enhanced T1-Weighted MRI for the Detection of Brain Metastases: 3D FSE versus 3D GRE-Based Sequences.AJNR. American journal of neuroradiology · 2025Article
- Efficacy of 3D-TSE sequence-based radiosurgery in prolonging time to distant intracranial failure: A session-wise analysis in a histology-diverse patient cohort.Neuro-oncology · 2025Article
- Review
- Longitudinal deep neural networks for assessing metastatic brain cancer on a large open benchmark.Nature communications · 2024Article
- Exploring the Impact of 3D Fast Spin Echo and Inversion Recovery Gradient Echo Sequences Magnetic Resonance Imaging Acquisition on Automated Brain Tumor Segmentation.Mayo Clinic proceedings. Digital health · 2024Article
- Where Does Auto-Segmentation for Brain Metastases Radiosurgery Stand Today?Bioengineering (Basel, Switzerland) · 2024Review
- Reducing false positives in deep learning-based brain metastasis detection by using both gradient-echo and spin-echo contrast-enhanced MRI: validation in a multi-center diagnostic cohort.European radiology · 2024Article
- Autoimmune encephalitis: what the radiologist needs to know.Neuroradiology · 2024Review
- Comparison between postcontrast thin-slice T1-weighted 2D spin echo and 3D T1-weighted SPACE sequences in the detection of brain metastases at 1.5 and 3 T.Insights into imaging · 2024Article
Corrections and comments
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Authors and funding
4 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to compare the detectability of brain metastases using contrast-enhanced spin-echo (SE) and gradient-echo (GRE) T1-weighted images. The Ovid-MEDLINE and EMBASE databases were searched for studies on the detectability of brain metastases using contrast-enhanced SE or GRE images. The pooled proportions for the detectability of brain metastases were assessed using random-effects modeling. Heterogeneity among studies was determined using χ (2) statistics for the pooled estimates and the inconsistency index, I (2) . To overcome heterogeneity, subgroup analyses according to slice thickness and lesion size were performed. A total of eight eligible studies, which included a sample size of 252 patients and 1413 brain metastases, were included. The detectability of brain metastases using SE images (89.2 %) was higher than using GRE images (81.6 %; adjusted 84.0 %), but this difference was not statistically significant (p = 0.2385). In subgroup analysis of studies with 1-mm-thick slices and small metastases (<5 mm in diameter), 3-dimensional (3D) SE images demonstrated a higher detectability in comparison to 3D GRE images (93.7 % vs 73.1 % in 1-mm-thick slices; 89.5 % vs 59.4 % for small metastases) (p < 0.0001). Although both SE or GRE images are acceptable for detecting brain metastases, contrast-enhanced 3D SE images using 1-mm-thick slices are preferred for detecting brain metastases, especially small lesions (<5 mm in diameter).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.