ArticleInsights into imaging2015
Medical imaging in personalised medicine: a white paper of the research committee of the European Society of Radiology (ESR).
Article in Insights into imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 2 of them syntheses 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
57 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Factors associated with pathologic myopia onset and progression: A systematic review and meta-analysis.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2024Pooled it
- Evaluation of background parenchymal enhancement on breast MRI: a systematic review.The British journal of radiology · 2017Pooled it
- Beyond radiotheranostics: how imaging modality defines theranostics.European radiology experimental · 2026Review
- Artificial intelligence in paediatric neuroradiology: current landscape, challenges, and future directions.Pediatric radiology · 2026Review
- The Environmental Impact of Medical Imaging Agents and the Roadmap to Sustainable Medical Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Editorial for the Special Issue "Imaging Diagnosis in the Abdomen"-A Step Forward in Diagnostic Precision.Diagnostics (Basel, Switzerland) · 2025Article
- Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer.Military Medical Research · 2024Review
- Cardiovascular Imaging in the Era of Precision Medicine: Insights from Advanced Technologies - A Narrative Review.Health science reports · 2024Article
- Radiomics for Predicting Prognostic Factors in Breast Cancer: Insights from Contrast-Enhanced Mammography (CEM).Journal of clinical medicine · 2024Article
- Precision Medicine in Cytopathology.Surgical pathology clinics · 2024Review
- The Utility of Three-Dimensional Printing in Physician-Modified Stent Grafts for Aortic Lesions Repair.Journal of clinical medicine · 2024Review
- Nuclear Cardiology in the Era of Precision Medicine: Tailoring Treatment to the Individual Patient.Cureus · 2024Review
- Review
- Novel genetic assessments for cancer patients: where does medical imaging stand in the future of personalised medicine?Journal of medical radiation sciences · 2024Article
- A Radiomic "Warning Sign" of Progression on Brain MRI in Individuals with MS.AJNR. American journal of neuroradiology · 2024Article
- Review
- Diagnostic Excellence in Pediatric Spine Imaging: Using Contextualized Imaging Protocols.Diagnostics (Basel, Switzerland) · 2023Review
- Integrating oculomics with genomics reveals imaging biomarkers for preventive and personalized prediction of arterial aneurysms.The EPMA journal · 2023Article
- Precision Medicine in Radiomics and Radiogenomics.Journal of personalized medicine · 2022Article
- Editorial on Special Issue "Quantitative PET and SPECT".Diagnostics (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The future of medicine lies in early diagnosis and individually tailored treatments, a concept that has been designated 'personalised medicine' (PM), which aims to deliver the right treatment to the right patient at the right time. Medical imaging has always been personalised and is fundamental to almost all aspects of PM. It is instrumental in solving clinical differential diagnoses. Imaging procedures are tailored to the clinical problem and patient characteristics. Screening for preclinical disease is done with imaging. Stratification based on imaging biomarkers can help identify individuals suited for preventive intervention. Treatment decisions are based on the in vivo visualisation of the location and extent of an abnormality, as well as the loco-regional physiological, biochemical and biological processes using structural and molecular imaging. Image-guided biopsy provides relevant tissue specimens for genetic/molecular characterisation. In addition, radiogenomics relate imaging biomarkers to these genetic and molecular features. Furthermore, imaging is essential to patient-tailored therapy planning, therapy monitoring and follow-up of disease, as well as targeting non-invasive or minimally invasive treatments, especially with the rise of theranostics. Radiologists need to be prepared for this new paradigm as it will mean changes in training, clinical practice and in research. Key Points • Medical imaging is a key component in personalised medicine • Personalised prevention will rely on image-based screening programmes • Anatomical, functional and molecular imaging biomarkers affect decisions on the type and intensity of treatment • Treatment response assessment with imaging will improve personalised treatment • Image-based invasive intervention integrates personalised diagnosis and personalised treatment.
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.