ArticleMedicine2018
Comparisons of the accuracy of radiation diagnostic modalities in brain tumor: A nonrandomized, nonexperimental, cross-sectional trial.
Article in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 15 citations in OpenAlex.
- Challenges and Advances in Classifying Brain Tumors: An Overview of Machine, Deep Learning, and Hybrid Approaches with Future Perspectives in Medical Imaging.Current medical imaging · 2025Review
- Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment.NPJ precision oncology · 2024Review
- A Review of Recent Advances in Brain Tumor Diagnosis Based on AI-Based Classification.Diagnostics (Basel, Switzerland) · 2023Review
- Review
- A Survey of Brain Tumor Segmentation and Classification Algorithms.Journal of imaging · 2021Article
- Diagnosing brain tumours by routine blood tests using machine learning.Scientific reports · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor morphology improved sensitivity, accuracy, and specificity of the diagnosis, but all diagnostic techniques have attenuation correction issues.To compare computed tomographic (CT), positron emission tomographic (PET), and magnetic resonance imaging (MRI) characteristics of patients with brain tumor in a Chinese setting.A nonrandomized, nonexperimental, cross-sectional trial.Jining No. 1 People's Hospital, China.In total, 127 patients who had clinically confirmed a brain tumor were included in the cross-sectional study. Patients were subjected to brain CT, MRI, and PET. The tumors resected after brain surgery were subjected to morphological diagnosis. Statistical analysis of data of surgically removed tumor and that of different methods of diagnosis was performed using Wilcoxon test following Tukey-Kramer test. Spearmen correlation was performed between diagnostic modalities and in vivo morphology. Results were considered significant at 99% of confidence level.The data of diameter and volume of tumor derived from CT (Spearman r = 0.9845 and 0.9706), and MRI (Spearman r = 0.955 and 0.2378) were failed to correlate with that of that of the surgically removed tumor. However, prediction of diameter and volume of the tumor by PET (Spearman r = 0.9922 and 0.9921) were correlated with that of the surgically removed tumor. CT and MRI were failed to quantified pituitary adenomas.The study was recommended PET for assessment of brain tumor.
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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.