ArticleJournal of radiation research2018
Radiomics and radiogenomics for precision radiotherapy.
Article in Journal of radiation research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.
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
51 citing papers in PubMed, 1 synthesis or guideline pooled it, 94 citations in OpenAlex.
- Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy.Seminars in cancer biology · 2022Pooled it
- Prognostic prediction of hypertensive intracerebral hemorrhage using CT radiomics and machine learning.Brain and behavior · 2021Trial
- Deep learning model based on automated CT image segmentation for predicting the optimal radiotherapy protocol in limited-stage small cell lung cancer patients: a multicenter study.Translational lung cancer research · 2026Article
- Data-driven strategies for immunoradiotherapy in uveal melanoma: the role of artificial intelligence.Frontiers in pharmacology · 2026Review
- Review
- Hearing Loss and Middle Ear Effusion in Nasopharyngeal Carcinoma Following Radiotherapy: Dose-Response Relationship and Normal Tissue Complication Probability Modeling.International archives of otorhinolaryngology · 2025Article
- Radiogenomic Landscape of Metastatic Endocrine-Positive Breast Cancer Resistant to Aromatase Inhibitors.Cancers · 2025Review
- CT-based radiomics integrated model for brain metastases in stage III/IV ALK-positive lung adenocarcinoma patients.Frontiers in oncology · 2025Article
- Radiomics in radiology: What the radiologist needs to know about technical aspects and clinical impact.La Radiologia medica · 2024Review
- The prognostic value of radiogenomics using CT in patients with lung cancer: a systematic review.Insights into imaging · 2024Review
- Utility of CT Radiomics and Delta Radiomics for Survival Evaluation in Locally Advanced Nasopharyngeal Carcinoma with Concurrent Chemoradiotherapy.Diagnostics (Basel, Switzerland) · 2024Article
- Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights.Nature communications · 2024Article
- Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept.Cell reports. Medicine · 2024Article
- Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence.Biology · 2023Review
- Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial Intelligence.Cancers · 2023Review
- A radiomics-based study for differentiating parasellar cavernous hemangiomas from meningiomas.Scientific reports · 2022Article
- High-dimensional role of AI and machine learning in cancer research.British journal of cancer · 2022Review
- Virtual Biopsy in Soft Tissue Sarcoma. How Close Are We?Frontiers in oncology · 2022Review
- Radiomics-Guided Precision Medicine Approaches for Colorectal Cancer.Frontiers in oncology · 2022Review
- Treatment-integrated imaging, radiomics, and personalised radiotherapy: the future is at hand.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Imaging plays an important role in the diagnosis and staging of cancer, as well as in radiation treatment planning and evaluation of therapeutic response. Recently, there has been significant interest in extracting quantitative information from clinical standard-of-care images, i.e. radiomics, in order to provide a more comprehensive characterization of image phenotypes of the tumor. A number of studies have demonstrated that a deeper radiomic analysis can reveal novel image features that could provide useful diagnostic, prognostic or predictive information, improving upon currently used imaging metrics such as tumor size and volume. Furthermore, these imaging-derived phenotypes can be linked with genomic data, i.e. radiogenomics, in order to understand their biological underpinnings or further improve the prediction accuracy of clinical outcomes. In this article, we will provide an overview of radiomics and radiogenomics, including their rationale, technical and clinical aspects. We will also present some examples of the current results and some emerging paradigms in radiomics and radiogenomics for clinical oncology, with a focus on potential applications in radiotherapy. Finally, we will highlight the challenges in the field and suggest possible future directions in radiomics to maximize its potential impact on precision radiotherapy.
Indexed as
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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.