ArticleScientific reports2021
Amide proton transfer weighted (APTw) imaging based radiomics allows for the differentiation of gliomas from metastases.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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
32 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.
- Detection of breast cancer lesions using APT weighted MRI: a systematic review.Journal of translational medicine · 2025Pooled it
- Radiomic correlates with overall survival in glioblastoma: amide proton transfer (APT) imaging-based feature analysis and integration of clinical factors.Physical and engineering sciences in medicine · 2026Article
- CEST MRI Processing Pipeline in Pilot Study of Alzheimer's Disease Patients.Magnetic resonance in medicine · 2026Article
- The explainability of radiomic-based machine learning models for brain glioma grading on amide proton transfer-weighted images.Scientific reports · 2026Article
- Chemical Exchange Saturation Transfer Imaging in Neuroinflammation: Methods, Challenges, and Recommendations.International journal of molecular sciences · 2025Review
- Novel non‑metal‑based contrast agents for MR imaging: Emerging approaches and clinical perspectives (Review).International journal of oncology · 2025Review
- The Pulseq-CEST Library: definition of preparations and simulations, example data, and example evaluations.Magma (New York, N.Y.) · 2025Article
- 3-Tesla amide proton transfer-weighted imaging (APT-WI): elevated signal also in tumor mimics.European radiology · 2025Article
- Predicting postoperative recurrence and survival in glioma patients using enhanced MRI-based delta habitat radiomics: an 8-year retrospective pilot study.World journal of surgical oncology · 2025Article
- Sub-region based histogram analysis of amide proton transfer-weighted MRI for predicting tumor budding grade in rectal adenocarcinoma: a prospective study.European radiology · 2025Article
- APT imaging of hepatocellular carcinoma signals an effective therapeutic response in advance of tumor shrinkage.Hepatic oncology · 2024Article
- MRI-Based Radiomics as a Promising Noninvasive Diagnostic Technique for Adenomyosis.Journal of clinical medicine · 2024Article
- Amide proton transfer weighted and diffusion weighted imaging based radiomics classification algorithm for predicting 1p/19q co-deletion status in low grade gliomas.BMC medical imaging · 2024Article
- Advances in diffuse glioma assessment: preoperative and postoperative applications of chemical exchange saturation transfer.Frontiers in neuroscience · 2024Review
- Review
- Review
- Multiparametric MRI: From Simultaneous Rapid Acquisition Methods and Analysis Techniques Using Scoring, Machine Learning, Radiomics, and Deep Learning to the Generation of Novel Metrics.Investigative radiology · 2023Review
- Advances in differential diagnosis of cerebrovascular diseases in magnetic resonance imaging: a narrative review.Quantitative imaging in medicine and surgery · 2023Review
- Radiomics analysis of amide proton transfer-weighted and structural MR images for treatment response assessment in malignant gliomas.NMR in biomedicine · 2023Article
- Differentiation of Glioblastoma and Brain Metastases by MRI-Based Oxygen Metabolomic Radiomics and Deep Learning.Metabolites · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We sought to evaluate the utility of radiomics for Amide Proton Transfer weighted (APTw) imaging by assessing its value in differentiating brain metastases from high- and low grade glial brain tumors. We retrospectively identified 48 treatment-naïve patients (10 WHO grade 2, 1 WHO grade 3, 10 WHO grade 4 primary glial brain tumors and 27 metastases) with either primary glial brain tumors or metastases who had undergone APTw MR imaging. After image analysis with radiomics feature extraction and post-processing, machine learning algorithms (multilayer perceptron machine learning algorithm; random forest classifier) with stratified tenfold cross validation were trained on features and were used to differentiate the brain neoplasms. The multilayer perceptron achieved an AUC of 0.836 (receiver operating characteristic curve) in differentiating primary glial brain tumors from metastases. The random forest classifier achieved an AUC of 0.868 in differentiating WHO grade 4 from WHO grade 2/3 primary glial brain tumors. For the differentiation of WHO grade 4 tumors from grade 2/3 tumors and metastases an average AUC of 0.797 was achieved. Our results indicate that the use of radiomics for APTw imaging is feasible and the differentiation of primary glial brain tumors from metastases is achievable with a high degree of accuracy.
Indexed as
Identifiers
What OpenQuestion holds
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.