ReviewClinical cancer research : an official journal of the American Association for Cancer Research2016
Quantitative Imaging in Cancer Clinical Trials.
Review in Clinical cancer research : an official journal of the American Association for Cancer Research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 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
69 citing papers in PubMed.
- Prospective evaluation of plasma Epstein-Barr virus DNA clearance and fluorodeoxyglucose positron emission scan in assessing early response to chemotherapy in patients with advanced or recurrent nasopharyngeal carcinoma.British journal of cancer · 2018Trial
- Monitoring early response to chemoradiotherapy withEuropean journal of nuclear medicine and molecular imaging · 2017Trial
- The Next Frontier in Quantitative Co-Clinical Imaging to Advance Functional Precision Oncology.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- Digital Twin Technology In Radiology.Journal of imaging informatics in medicine · 2026Review
- Extending Regression Without Truth to Integrate Ground-Truth Measurements for Evaluating Quantitative Imaging Methods with Patient Data.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Comparing evaluation of quantitative imaging methods using reference standards versus regression‑without‑truth‑based technique.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Lanthanide Nanotheranostics in Radiotherapy.International journal of molecular sciences · 2025Review
- Quantitative evaluation of apparent diffusion coefficient in a large multi-unit institution.Physics and imaging in radiation oncology · 2025Article
- Repeatability and Reproducibility of Pseudocontinuous Arterial Spin-Labeling-Measured Brain Perfusion in Healthy Volunteers and Patients with Glioblastoma.AJNR. American journal of neuroradiology · 2025Article
- Image biomarkers and explainable AI: handcrafted features versus deep learned features.European radiology experimental · 2024Review
- Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantom.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Magnetic resonance imaging-based radiomics was used to evaluate the level of prognosis-related immune cell infiltration in breast cancer tumor microenvironment.BMC medical imaging · 2024Article
- Initial experience in implementing quantitative DCE-MRI to predict breast cancer therapy response in a multi-center and multi-vendor platform setting.Frontiers in oncology · 2024Article
- Toward Practical Integration of Omic and Imaging Data in Co-Clinical Trials.Tomography (Ann Arbor, Mich.) · 2023Article
- An untrained deep learning method for reconstructing dynamic MR images from accelerated model-based data.Magnetic resonance in medicine · 2023Article
- Analysis of simplicial complexes to determine when to sample for quantitative DCE MRI of the breast.Magnetic resonance in medicine · 2023Article
- Quantitative DCE-MRI prediction of breast cancer recurrence following neoadjuvant chemotherapy: a preliminary study.BMC medical imaging · 2022Article
- Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy.Advanced drug delivery reviews · 2022Review
- Dynamic characterization of breast cancer response to neoadjuvant therapy using biophysical metrics of spatial proliferation.Scientific reports · 2022Article
- Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness.Journal of magnetic resonance imaging : JMRI · 2022Article
9 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
19 authors.
Funding
Abstract
As anticancer therapies designed to target specific molecular pathways have been developed, it has become critical to develop methods to assess the response induced by such agents. Although traditional, anatomic CT, and MRI examinations are useful in many settings, increasing evidence suggests that these methods cannot answer the fundamental biologic and physiologic questions essential for assessment and, eventually, prediction of treatment response in the clinical trial setting, especially in the critical period soon after treatment is initiated. To optimally apply advances in quantitative imaging methods to trials of targeted cancer therapy, new infrastructure improvements are needed that incorporate these emerging techniques into the settings where they are most likely to have impact. In this review, we first elucidate the needs for therapeutic response assessment in the era of molecularly targeted therapy and describe how quantitative imaging can most effectively provide scientifically and clinically relevant data. We then describe the tools and methods required to apply quantitative imaging and provide concrete examples of work making these advances practically available for routine application in clinical trials. We conclude by proposing strategies to surmount barriers to wider incorporation of these quantitative imaging methods into clinical trials and, eventually, clinical practice. Our goal is to encourage and guide the oncology community to deploy standardized quantitative imaging techniques in clinical trials to further personalize care for cancer patients and to provide a more efficient path for the development of improved targeted therapies.
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.