ArticleClinical cancer research : an official journal of the American Association for Cancer Research2021
Diffusion-weighted Imaging Allows for Downgrading MR BI-RADS 4 Lesions in Contrast-enhanced MRI of the Breast to Avoid Unnecessary Biopsy.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 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
46 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Diffusion-Weighted MRI for the Assessment of Molecular Prognostic Biomarkers in Breast Cancer.Korean journal of radiology · 2024Pooled it
- Economic evaluation of breast MRI in screening - a systematic review and basic approach to cost-effectiveness analyses.Frontiers in oncology · 2023Pooled it
- Combined diagnosis of multiparametric MRI-based deep learning models facilitates differentiating triple-negative breast cancer from fibroadenoma magnetic resonance BI-RADS 4 lesions.Journal of cancer research and clinical oncology · 2023Trial
- Additional diagnostic value of lesion visibility on diffusion-weighted imaging for differentiating BI-RADS category 4 MRI-detected breast lesions.Japanese journal of radiology · 2026Article
- Fine-tuned multimodal GPT-4o for generating diagnostic impressions in breast magnetic resonance imaging: insights into non-mass enhancement lesions.Quantitative imaging in medicine and surgery · 2026Article
- Establishing an Evidence-based Modern Breast MRI Program.Journal of breast imaging · 2026Review
- An interpretable AI system reduces false-positive MRI diagnoses by stratifying high-risk breast lesions.Nature communications · 2026Article
- Article
- Integrated [European journal of nuclear medicine and molecular imaging · 2026Article
- Reducing breast biopsy at MRI: comparison of minimum ADC cutoff and mean ADC cutoff identified by the ECOG-ACRIN A6702 multicenter trial.BMC cancer · 2025Article
- Multimodal ultrasound to predict central cervical lymph node metastasis in clinically lymph node-negative differentiated thyroid carcinomas: a two-center retrospective study.Gland surgery · 2025Article
- Histogram analysis of relaxometry from synthetic MRI for differentiation of breast BI-RADS 4 non-mass enhancement lesions.BMC medical imaging · 2025Article
- Reduction of biopsy rate in BI-RADS4 breast lesions: potential of an abbreviated advanced DWI protocol.European radiology · 2025Article
- Time to Enhancement Measured From Ultrafast Dynamic Contrast-Enhanced MRI for Improved Breast Lesion Diagnosis.Journal of breast imaging · 2025Article
- Breast Diffusion-weighted MR Imaging: Current Applications, Insights from Screening, and Future Directions.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Review
- An Updated Systematic Review and Meta-Analysis of Diagnostic Accuracy of Dynamic Contrast Enhancement and Diffusion-Weighted MRI in Differentiating Benign and Malignant Non-Mass Enhancement Lesions.Journal of clinical medicine · 2025Review
- Preoperative Diagnosis of Ipsilateral and Contralateral Breast Cancer: Role of Diffusion-weighted MRI.Radiology · 2025Article
- Exploring MRI and Mammography Lesion Features for Breast Cancer Detection in PTEN Hamartoma Tumor Syndrome.Cancers · 2025Article
- Standardization and advancements efforts in breast diffusion-weighted imaging.Japanese journal of radiology · 2025Review
- Quantitative MR Imaging of the Breast.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
purposeDiffusion-weighted imaging with the calculation of an apparent diffusion coefficient (ADC) has been proposed as a quantitative biomarker on contrast-enhanced MRI (CE-MRI) of the breast. There is a need to approve a generalizable ADC cutoff. The purpose of this study was to evaluate whether a predefined ADC cutoff allows downgrading of BI-RADS 4 lesions on CE-MRI, avoiding unnecessary biopsies. EXPERIMENTAL
designThis was a retrospective, multicentric, cross-sectional study. Data from five centers were pooled on the individual lesion level. Eligible patients had a BI-RADS 4 rating on CE-MRI. For each center, two breast radiologists evaluated the images. Data on lesion morphology (mass, non-mass), size, and ADC were collected. Histology was the standard of reference. A previously suggested ADC cutoff (≥1.5 × 10
resultsThere were 657 female patients (mean age, 42; SD, 14.1) with 696 BI-RADS 4 lesions included. Disease prevalence was 59.5% (414/696). The area under the ROC curve was 0.784. Applying the investigated ADC cutoff, sensitivity was 96.6% (400/414). The potential reduction of unnecessary biopsies was 32.6% (92/282).
conclusionsAn ADC cutoff of ≥1.5 × 10
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.