ReviewClinical cancer research : an official journal of the American Association for Cancer Research2015
Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome.
Review in Clinical cancer research : an official journal of the American Association for Cancer Research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 400 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
400 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Mastering CT-based radiomic research in lung cancer: a practical guide from study design to critical appraisal.The British journal of radiology · 2025Guideline
- Visualising spatial heterogeneity in glioblastoma using imaging habitats.Frontiers in oncology · 2022Pooled it
- Vessel size and perfusion-derived vascular habitat refines prediction of treatment failure to bevacizumab in recurrent glioblastomas: validation in a prospective cohort.European radiology · 2023Trial
- Preoperative contrast-enhanced computed tomography-based radiomics model for overall survival prediction in hepatocellular carcinoma.World journal of gastroenterology · 2022Trial
- A Machine Learning Model Based on Unsupervised Clustering Multihabitat to Predict the Pathological Grading of Meningiomas.BioMed research international · 2022Trial
- MRI-based preoperative WHO grade prediction in meningioma: development and comparison of deep learning, radiomics, clinical, and combined models in multicenter data.Journal of neuro-oncology · 2026Article
- CT radiomics and topology-based intratumoral heterogeneity for preoperative prediction of nuclear β-catenin expression in hepatocellular carcinoma.Abdominal radiology (New York) · 2026Article
- DCE-MRI histogram analysis for predicting survival in patients with epithelial ovarian carcinoma.Abdominal radiology (New York) · 2026Article
- First Clinical-Scale Use of a Percutaneous EPR Oxygen Probe (OxyTrack) for Deep-Tissue pOMagnetic resonance in medicine · 2026Article
- NNMT-associated metabolic-thromboinflammatory-immune co-activation in heterogeneous CTC clusters: a hypothesis-generating computational framework".BMC cancer · 2026Article
- Comprehensive Radiomics Analysis to Enhance Breast Lesion Characterization Using QUS Spectral Parametric Imaging.Cancers · 2026Article
- Interpretable habitat radiomics based nomogram for predicting T790M mutation in non-small cell lung cancer with brain metastases.Quantitative imaging in medicine and surgery · 2026Article
- Precision Risk Stratification in Prostate Cancer: Unveiling MRI-Based Habitat-Driven Radiomics Model for Enhanced Treatment Guidance.Journal of imaging informatics in medicine · 2026Article
- Article
- Distinguishing Molecular and Histologic Glioblastomas Using Multiparametric MRI-Based Habitat Analysis.Korean journal of radiology · 2026Article
- MRI-based perfusion-diffusion habitat analysis for characterizing intratumoral heterogeneity in rectal adenocarcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Review
- Preoperative assessment of intratumor heterogeneity using intravoxel incoherent motion MRI for survival prediction in high-grade gliomas: a feasibility study.BMC medical imaging · 2026Article
- Development and validation: a whole-tumor histogram model based on intravoxel incoherent motion diffusion-weighted imaging for diagnosing tumor deposits in rectal cancer.Abdominal radiology (New York) · 2026Article
- Predicting response to neoadjuvant chemotherapy combined with immunotherapy in gastric cancer based on habitat imaging and peritumoral radiomics: a two-center study.Journal of translational medicine · 2026Article
340 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Tumors exhibit genomic and phenotypic heterogeneity, which has prognostic significance and may influence response to therapy. Imaging can quantify the spatial variation in architecture and function of individual tumors through quantifying basic biophysical parameters such as CT density or MRI signal relaxation rate; through measurements of blood flow, hypoxia, metabolism, cell death, and other phenotypic features; and through mapping the spatial distribution of biochemical pathways and cell signaling networks using PET, MRI, and other emerging molecular imaging techniques. These methods can establish whether one tumor is more or less heterogeneous than another and can identify subregions with differing biology. In this article, we review the image analysis methods currently used to quantify spatial heterogeneity within tumors. We discuss how analysis of intratumor heterogeneity can provide benefit over more simple biomarkers such as tumor size and average function. We consider how imaging methods can be integrated with genomic and pathology data, instead of being developed in isolation. Finally, we identify the challenges that must be overcome before measurements of intratumoral heterogeneity can be used routinely to guide patient care.
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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.