ArticleCancers2022
Diffusion Weighted Imaging in Gliomas: A Histogram-Based Approach for Tumor Characterization.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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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.
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Who cites it
17 citing papers in PubMed, 26 citations in OpenAlex.
- DCE-MRI and Mammography integrated radiomic analysis in triple negative ductal invasive breast cancer patients. Comparison between BRCA and not BRCA mutated patients: preliminary results.European journal of radiology open · 2026Article
- Histogram Analysis and Heterogeneous Radial Changes Using ADC Map Images in Metastatic Brain Tumors for Dose Painting Intent.Advanced biomedical research · 2026Article
- Association between histogram parameters of T2 weighted MRI data, WHO grade, tumor proliferation index and selected molecular markers in low-grade glioma.Frontiers in radiology · 2026Article
- Histogram analysis of IVIM MRI for differentiating glioma IDH-1 status, grade, and Ki-67 expression: a comparison of bi-exponential models at multiple B-value.BMC medical imaging · 2025Article
- Article
- Advanced MRI, Radiomics and Radiogenomics in Unravelling Incidental Glioma Grading and Genetic Status: Where Are We?Medicina (Kaunas, Lithuania) · 2025Review
- MRI radiomics based on machine learning in high-grade gliomas as a promising tool for prediction of CD44 expression and overall survival.Scientific reports · 2025Article
- Preoperative prediction of IDH genotypes and prognosis in adult-type diffuse gliomas: intratumor heterogeneity habitat analysis using dynamic contrast-enhanced MRI and diffusion-weighted imaging.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Assessment of MGMT and TERT Subtypes and Prognosis of Glioblastoma by Whole Tumor Apparent Diffusion Coefficient Histogram Analysis.Brain and behavior · 2025Article
- Comparison Between Visual Assessment and Apparent Diffusion Coefficient (ADC) Value Measurement on Diffusion Weighted Imaging (DWI) in Supratentorial Glioma Grading in Children.Medical archives (Sarajevo, Bosnia and Herzegovina) · 2025Article
- Review
- Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas.Frontiers in oncology · 2024Article
- MRI radiomics model for predicting TERT promoter mutation status in glioblastoma.Brain and behavior · 2023Article
- Magnetic Resonance Imaging of Primary Adult Brain Tumors: State of the Art and Future Perspectives.Biomedicines · 2023Review
- Multi-b-value diffusion stretched-exponential model parameters correlate with MIB-1 and CD34 expression in Glioma patients, an intraoperative MR-navigated, biopsy-based histopathologic study.Frontiers in oncology · 2023Article
- Wall characteristics of atherosclerotic middle cerebral arteries in patients with single or multiple infarcts: A high-resolution MRI Study.Frontiers in neurology · 2022Article
- Apparent diffusion coefficient for genetic characterization of untreated adult gliomas: A meta-analysis stratified by methods.Neuro-oncology advancesArticle
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
(1) Background: Astrocytic gliomas present overlapping appearances in conventional MRI. Supplementary techniques are necessary to improve preoperative diagnostics. Quantitative DWI via the computation of apparent diffusion coefficient (ADC) histograms has proven valuable for tumor characterization and prognosis in this regard. Thus, this study aimed to investigate (I) the potential of ADC histogram analysis (HA) for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and (II) whether those parameters are associated with Ki-67 immunolabelling, the isocitrate-dehydrogenase-1 (IDH1) mutation profile and the methylguanine-DNA-methyl-transferase (MGMT) promoter methylation profile; (2) Methods: The ADC-histograms of 82 gliomas were computed. Statistical analysis was performed to elucidate associations between histogram features and WHO grade, Ki-67 immunolabelling, IDH1 and MGMT profile; (3) Results: Minimum, lower percentiles (10th and 25th), median, modus and entropy of the ADC histogram were significantly lower in HGG. Significant differences between IDH1-mutated and IDH1-wildtype gliomas were revealed for maximum, lower percentiles, modus, standard deviation (SD), entropy and skewness. No differences were found concerning the MGMT status. Significant correlations with Ki-67 immunolabelling were demonstrated for minimum, maximum, lower percentiles, median, modus, SD and skewness; (4) Conclusions: ADC HA facilitates non-invasive prediction of the WHO grade, tumor-proliferation rate and clinically significant mutations in case of astrocytic gliomas.
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Registered trials
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