ReviewNature reviews. Clinical oncology2014
Quantitative multimodality imaging in cancer research and therapy.
Review in Nature reviews. Clinical oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 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
65 citing papers in PubMed.
- Multiparametric imaging of patient and tumour heterogeneity in non-small-cell lung cancer: quantification of tumour hypoxia, metabolism and perfusion.European journal of nuclear medicine and molecular imaging · 2016Trial
- Preparation of an activatable benzothiadiazole-based nanoprobe for multispectral optoacoustic and NIR-II fluorescence dual-mode imaging of liver injury.Nature protocols · 2026Review
- Multimodal Integration in Health Care: Development With Applications in Disease Management.Journal of medical Internet research · 2025Review
- Activatable second-near-infrared-window multimodal luminogens with aggregation-induced-emission and aggregation-caused-quenching properties for step-imaging guided tumor therapy.Nature communications · 2025Article
- A multimodal machine learning model for the stratification of breast cancer risk.Nature biomedical engineering · 2025Article
- Ultra-fast light-field microscopy with event detection.Light, science & applications · 2024Article
- Engineering Heterogeneous Tumor Models for Biomedical Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Article
- Multimodal prediction of neoadjuvant treatment outcome by serial FDG PET and MRI in women with locally advanced breast cancer.Breast cancer research : BCR · 2023Article
- Omniparticle Contrast Agent for Multimodal Imaging: Synthesis and Characterization in an Animal Model.Molecular imaging and biology · 2023Article
- Mathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma.Scientific reports · 2023Article
- Multimodal analysis methods in predictive biomedicine.Computational and structural biotechnology journal · 2023Review
- Towards differentiation of brain tumor from radiation necrosis using multi-parametric MRI: Preliminary results at 4.7 T using rodent models.Magnetic resonance imaging · 2022Article
- MRI techniques for immunotherapy monitoring.Journal for immunotherapy of cancer · 2022Review
- Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy.Advanced drug delivery reviews · 2022Review
- Criteria for the design of tissue-mimicking phantoms for the standardization of biophotonic instrumentation.Nature biomedical engineering · 2022Review
- Quantifying Tumor Heterogeneity via MRI Habitats to Characterize Microenvironmental Alterations in HER2+ Breast Cancer.Cancers · 2022Article
- Iron-Gold Nanoflowers: A Promising Tool for Multimodal Imaging and Hyperthermia Therapy.Pharmaceutics · 2022Article
- Cross-Modality Imaging of Murine Tumor Vasculature-a Feasibility Study.Molecular imaging and biology · 2021Article
- Multi-scale optoacoustic molecular imaging of brain diseases.European journal of nuclear medicine and molecular imaging · 2021Review
5 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Advances in hardware and software have enabled the realization of clinically feasible, quantitative multimodality imaging of tissue pathophysiology. Earlier efforts relating to multimodality imaging of cancer have focused on the integration of anatomical and functional characteristics, such as PET-CT and single-photon emission CT (SPECT-CT), whereas more-recent advances and applications have involved the integration of multiple quantitative, functional measurements (for example, multiple PET tracers, varied MRI contrast mechanisms, and PET-MRI), thereby providing a more-comprehensive characterization of the tumour phenotype. The enormous amount of complementary quantitative data generated by such studies is beginning to offer unique insights into opportunities to optimize care for individual patients. Although important technical optimization and improved biological interpretation of multimodality imaging findings are needed, this approach can already be applied informatively in clinical trials of cancer therapeutics using existing tools. These concepts are discussed herein.
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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.