ReviewJournal of biomedicine & biotechnology2011
Quantifying tumor vascular heterogeneity with dynamic contrast-enhanced magnetic resonance imaging: a review.
Review in Journal of biomedicine & biotechnology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
56 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Quantification of heterogeneity as a biomarker in tumor imaging: a systematic review.PloS one · 2014Pooled it
- Multimodal radiomics incorporating intratumoral heterogeneity for prognostic assessment of metastatic outcomes in invasive breast cancer.Breast cancer research : BCR · 2026Article
- Parametric maps of spatial two-tissue compartment model for prostate dynamic contrast enhanced MRI - comparison with the standard tofts model in the diagnosis of prostate cancer.Physical and engineering sciences in medicine · 2023Article
- A proof-of-concept pipeline to guide evaluation of tumor tissue perfusion by dynamic contrast-agent imaging: Direct simulation and inverse tracer-kinetic procedures.Frontiers in bioinformatics · 2023Article
- DiffusionCT: Latent Diffusion Model for CT Image Standardization.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- A review on advances inInsights into imaging · 2022Review
- Contrast-enhanced ultrasonography for early prediction of response of neoadjuvant chemotherapy in breast cancer.Frontiers in oncology · 2022Article
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- Article
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- Cross-Vendor CT Image Data Harmonization Using CVH-CT.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Imaging Hallmarks of the Tumor Microenvironment in Glioblastoma Progression.Frontiers in oncology · 2021Article
- Texture Analysis of Breast DCE-MRI Based on Intratumoral Subregions for Predicting HER2 2+ Status.Frontiers in oncology · 2020Article
- Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials.Journal of magnetic resonance imaging : JMRI · 2019Review
- Phantom Validation of DCE-MRI Magnitude and Phase-Based Vascular Input Function Measurements.Tomography (Ann Arbor, Mich.) · 2019Article
- Radiomics in Kidney Cancer: MR Imaging.Magnetic resonance imaging clinics of North America · 2019Review
- The use of texture-based radiomics CT analysis to predict outcomes in early-stage non-small cell lung cancer treated with stereotactic ablative radiotherapy.The British journal of radiology · 2019Article
- Article
- [Prediction of the therapeutic response after target-combined chemotherapy treatment for patients with liver metastasis from colorectal cancer using computed tomography texture analysis].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2018Article
- Functional Parameters Derived from Magnetic Resonance Imaging Reflect Vascular Morphology in Preclinical Tumors and in Human Liver Metastases.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor microvasculature possesses a high degree of heterogeneity in its structure and function. These features have been demonstrated to be important for disease diagnosis, response assessment, and treatment planning. The exploratory efforts of quantifying tumor vascular heterogeneity with DCE-MRI have led to promising results in a number of studies. However, the methodological implementation in those studies has been highly variable, leading to multiple challenges in data quality and comparability. This paper reviews several heterogeneity quantification methods, with an emphasis on their applications on DCE-MRI pharmacokinetic parametric maps. Important methodological and technological issues in experimental design, data acquisition, and analysis are also discussed, with the current opportunities and efforts for standardization highlighted.
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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.