ArticleFrontiers in oncology2023
Heterogeneity matching and IDH prediction in adult-type diffuse gliomas: a DKI-based habitat analysis.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 16 citations in OpenAlex.
- Imaging tumor microenvironment heterogeneity in oral squamous cell carcinoma using IVIM DWI habitat analysis.European radiology experimental · 2026Article
- Application of a multimodal MRI model integrating radiomics and habitat features for predicting glioma pathology and prognosis.BMC medical imaging · 2026Article
- Habitat imaging based on water-fat separation for interpreting extraocular muscle heterogeneity in thyroid eye disease.European thyroid journal · 2026Article
- Cellularity habitat-based MRI radiomics for non-invasive grading and IDH mutation prediction in adult-type diffuse glioma.BMC medical imaging · 2026Article
- Integrated Radiomics Model Combining Diffusion Kurtosis Imaging and Dynamic Contrast-Enhanced MRI for Predicting TERT Promoter Mutation Status in Gliomas.Human mutation · 2026Article
- Evaluate lymphovascular space invasion in endometrial cancer using diffusion-weighted imaging-based habitat imaging.Scientific reports · 2025Article
- Preoperatively Predicting PIT1 Expression in Pituitary Adenomas Using Habitat, Intra-tumoral and Peri-tumoral Radiomics Based on MRI.Journal of imaging informatics in medicine · 2025Article
- Evidence gap in predicting intracranial haemorrhage risk in people with glioma on anticoagulants: a scoping review.BMC neurology · 2025Article
- Habitat subregions analysis based on neurite orientation dispersion and density imaging enhances isocitrate dehydrogenase genotyping in glioma.BMC medical imaging · 2025Article
- The value of morphological magnetic resonance imaging features combined with diffusion kurtosis imaging for predicting Ki-67 expression levels in high-grade gliomas.Quantitative imaging in medicine and surgery · 2025Article
- MRI-based habitat imaging predicts high-risk molecular subtypes and early risk assessment of lower-grade gliomas.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Improving Diagnostic Performance for Head and Neck Tumors with Simple Diffusion Kurtosis Imaging and Machine Learning Bi-Parameter Analysis.Diagnostics (Basel, Switzerland) · 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
- Baseline MRI habitat imaging for predicting treatment response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.Frontiers in oncology · 2025Article
- Computed tomography radiomics reveals prognostic value of immunophenotyping in laryngeal squamous cell carcinoma: a comparison of whole tumor- versus habitats-based approaches.BMC medical imaging · 2024Article
- Diffusion kurtosis imaging-based habitat analysis identifies high-risk molecular subtypes and heterogeneity matching in diffuse gliomas.Annals of clinical and translational neurology · 2024Article
- Novel Imaging Approaches for Glioma Classification in the Era of the World Health Organization 2021 Update: A Scoping Review.Cancers · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To explain adult-type diffuse gliomas heterogeneity through diffusion kurtosis imaging-based habitat characteristics and develop and validate a comprehensive model for predicting isocitrate dehydrogenase (IDH) status. Materials and methods: In this prospective secondary analysis, 103 participants (mean age, 52 years; range, 21-77; 54 [52%] male) pathologically diagnosed with adult-type diffuse gliomas were enrolled between June 2018 and February 2022. The Otsu method was used to generate habitat maps with mean diffusivity (MD) and mean kurtosis (MK) for a total of 4 subhabitats containing 16 habitat features. Habitat heatmaps were created based on the Pearson correlation coefficient. The Habitat imAging aNd clinicraD INtegrated prEdiction SyStem (HANDINESS) was created by combining clinical features, conventional MRI morphological features, and habitat image features. ROC, calibration curve, and decision curve analyses were used to select the optimal model after 32 pipelines for model training and validation. Results: In the restricted diffusion and high-density subhabitat, MK was highly correlated with MD (R Conclusion: Diffusion kurtosis imaging-based habitat analysis provides additional important information on microscopic tumor spatial heterogeneity. The HANDINESS has higher diagnostic performance and robustness than single-modality models.
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.