ArticleJournal of the National Cancer Institute. Monographs2015
Multiparametric and Multimodality Functional Radiological Imaging for Breast Cancer Diagnosis and Early Treatment Response Assessment.
Article in Journal of the National Cancer Institute. Monographs, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 18 citations in OpenAlex.
- Impact of continuous learning on diagnostic breast MRI AI: evaluation on an independent clinical dataset.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- A Review of the Role of the S-Detect Computer-Aided Diagnostic Ultrasound System in the Evaluation of Benign and Malignant Breast and Thyroid Masses.Medical science monitor : international medical journal of experimental and clinical research · 2021Review
- Review
- Article
- Multiparametric deep learning tissue signatures for a radiological biomarker of breast cancer: Preliminary results.Medical physics · 2020Article
- The Evolving Role of FDG-PET/CT in the Diagnosis, Staging, and Treatment of Breast Cancer.Molecular imaging and biology · 2019Review
- Imaging Considerations and Interprofessional Opportunities in the Care of Breast Cancer Patients in the Neoadjuvant Setting.Seminars in oncology nursing · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Breast cancer is the second leading cause of cancer death among US women, and the chance of a woman developing breast cancer sometime during her lifetime is one in eight. Early detection and diagnosis to allow appropriate locoregional and systemic treatment are key to improve the odds of surviving its diagnosis. Emerging data also suggest that different breast cancer subtypes (phenotypes) may respond differently to available adjuvant therapies. There is a growing understanding that not all patients benefit equally from systemic therapies, and therapeutic approaches are being increasingly personalized based on predictive biomarkers of clinical benefit. Optimal use of established and novel radiological imaging methods, such as magnetic resonance imaging and positron emission tomography, which have different biophysical mechanisms can simultaneously identify key functional parameters. These methods provide unique multiparametric radiological signatures of breast cancer, that will improve the accuracy of early diagnosis, help select appropriate therapies for early stage disease, and allow early assessment of therapeutic benefit.
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.