ReviewWorld journal of clinical oncology2014
Magnetic resonance imaging in breast cancer: A literature review and future perspectives.
Review in World journal of clinical oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 4 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
61 citing papers in PubMed, 4 syntheses or guidelines pooled it, 179 citations in OpenAlex.
- The effect of pre-operative MRI on the in-breast tumor recurrence rate of patients with breast cancer: a meta-analysis.Langenbeck's archives of surgery · 2025Pooled it
- Is radiomic MRI a feasible alternative to OncotypeDX® recurrence score testing? A systematic review and meta-analysis.BJS open · 2021Pooled it
- Preoperative breast magnetic resonance imaging in patients with ductal carcinoma in situ: a systematic review for the European Commission Initiative on Breast Cancer (ECIBC).European radiology · 2021Pooled it
- 1H-MRS evaluation of breast lesions by using total choline signal-to-noise ratio as an indicator of malignancy: a meta-analysis.Medical oncology (Northwood, London, England) · 2015Pooled it
- Tumor Biomechanics Quantified Using MR Elastography to Predict Response to Neoadjuvant Chemotherapy in Individuals with Breast Cancer.Radiology. Imaging cancer · 2025Trial
- Third-look ultrasound for breast MRI-only lesions undetectable on second-look ultrasound using conventional B-mode alone.Journal of medical ultrasonics (2001) · 2025Article
- Monitoring Pharmacological Treatment of Breast Cancer with MRI.Current issues in molecular biology · 2025Review
- MRI Radiomics Signatures of 21-Gene Recurrence Score for Predicting Survival in ER+/HER2- Breast Cancer.Cancer medicine · 2025Article
- Characterizing Breast Tumor Heterogeneity Through IVIM-DWI Parameters and Signal Decay Analysis.Diagnostics (Basel, Switzerland) · 2025Article
- Chemical Nose-Based Non-Invasive Detection of Breast Cancer Using Exhaled Breath.Sensors (Basel, Switzerland) · 2025Article
- Roles of artificial intelligence and high frame-rate contrast-enhanced ultrasound in the differential diagnosis of Breast Imaging Reporting and Data System 4 breast nodules.Gland surgery · 2025Article
- Validation of subpixel target detection and linear spectral unmixing techniques on short-wave infrared hyperspectral images of collagen phantoms.Journal of biomedical optics · 2025Article
- Employing Raman Spectroscopy and Machine Learning for the Identification of Breast Cancer.Biological procedures online · 2024Article
- Review
- In vivo lymph node CEST-Dixon MRI in breast cancer patients with metastatic lymph node involvement.Magnetic resonance in medicine · 2024Article
- Evaluation of Features in Probably Benign and Malignant Nonmass Enhancement in Breast MRI.International journal of breast cancer · 2024Article
- Towards a fast PET/MRI protocol for breast cancer imaging: maintaining diagnostic confidence while reducing PET and MRI acquisition times.European radiology · 2023Article
- MRI-Based Radiomics Approach Predicts Tumor Recurrence in ER + /HER2 - Early Breast Cancer Patients.Journal of digital imaging · 2023Article
- False-positive incidental lesions detected on contrast-enhanced breast MRI: clinical and imaging features.Breast cancer research and treatment · 2023Article
- A Hybrid Machine Learning Approach to Screen Optimal Predictors for the Classification of Primary Breast Tumors from Gene Expression Microarray Data.Diagnostics (Basel, Switzerland) · 2023Article
1 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
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early detection and diagnosis of breast cancer are essential for successful treatment. Currently mammography and ultrasound are the basic imaging techniques for the detection and localization of breast tumors. The low sensitivity and specificity of these imaging tools resulted in a demand for new imaging modalities and breast magnetic resonance imaging (MRI) has become increasingly important in the detection and delineation of breast cancer in daily practice. However, the clinical benefits of the use of pre-operative MRI in women with newly diagnosed breast cancer is still a matter of debate. The main additional diagnostic value of MRI relies on specific situations such as detecting multifocal, multicentric or contralateral disease unrecognized on conventional assessment (particularly in patients diagnosed with invasive lobular carcinoma), assessing the response to neoadjuvant chemotherapy, detection of cancer in dense breast tissue, recognition of an occult primary breast cancer in patients presenting with cancer metastasis in axillary lymph nodes, among others. Nevertheless, the development of new MRI technologies such as diffusion-weighted imaging, proton spectroscopy and higher field strength 7.0 T imaging offer a new perspective in providing additional information in breast abnormalities. We conducted an expert literature review on the value of breast MRI in diagnosing and staging breast cancer, as well as the future potentials of new MRI technologies.
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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.