ReviewCell reports. Medicine2024
Radiomics in breast cancer: Current advances and future directions.
Review in Cell reports. Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 156 papers, 3 of them syntheses that pooled it.
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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.
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Who cites it
156 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Radiomics for predicting microsatellite instability-high status in colorectal cancer: a systematic review and meta-analysis.World journal of surgical oncology · 2026Pooled it
- Deciphering the biological underpinnings behind prognostic MRI-based imaging signatures in breast cancer: a systematic review.Journal of translational medicine · 2025Pooled it
- 18F-FDG PET/CT Semiquantitative and Radiomic Features for Assessing Pathologic Axillary Lymph Node Status in Clinical Stage I-III Breast Cancer Patients: A Systematic Review.Current oncology (Toronto, Ont.) · 2025Pooled it
- DCE-MRI and Mammography integrated radiomic analysis in triple negative ductal invasive breast cancer patients. Comparison between BRCA and not BRCA mutated patients: preliminary results.European journal of radiology open · 2026Article
- Programmable Organic APharmaceutics · 2026Article
- Identifying breast cancer subtypes and exploring spatial expression patterns of the key subtype-specific gene based on pathological images, single-cell sequencing, and spatial transcriptomic data.Breast cancer (Tokyo, Japan) · 2026Article
- MRI-based habitat radiomics for assessing synchronous metastatic risk in renal cell carcinoma: a multicenter study.Abdominal radiology (New York) · 2026Article
- MRI-based radiomics with SHAP interpretation for preoperative prediction of upstaging in ductal carcinomaTranslational cancer research · 2026Article
- Intratumoral and peritumoral-based radiomics for assessment of lymphovascular invasion in invasive breast cancer: model development and validation.Translational cancer research · 2026Article
- Radiomic Characterization of Breast Tissue from Breast CT Images Obtained with Synchrotron Beams.Tomography (Ann Arbor, Mich.) · 2026Article
- Cancer-associated adipocytes: metabolic reprogramming, crosstalk and therapeutic implications in tumor progression.Signal transduction and targeted therapy · 2026Review
- A Parsimonious Ultrasound Radiomics and Ki-67 Model for Estimating MammaPrint Risk Categorization in HR+/HER2- Early Breast Cancer.Current oncology (Toronto, Ont.) · 2026Article
- Interpretable machine learning model integrating delta-radiomics enhances postoperative recurrence prediction in early-stage lung adenocarcinoma.Journal of thoracic disease · 2026Article
- Bridging In Vitro and Murine Breast Cancer Models: Advanced Imaging Across Multiscale Experimental Platforms.Cancers · 2026Review
- Integrating MRI radiomics and deep learning for predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer: a multicenter study.BMC medical imaging · 2026Article
- Deep learning-based classification of gh-secreting pituitary neuroendocrine tumors granulation patterns using H&E-stained histopathology.BMC endocrine disorders · 2026Article
- The role of artificial intelligence in precision medicine for breast cancer.Discover oncology · 2026Review
- Prediction of pathological complete response to neoadjuvant therapy in breast cancer integrating intratumoral and peritumoral delta radiomics with clinical features: a study based on multiparametric MRI.BMC medical imaging · 2026Article
- Automatic segmentation-based radiomics and deep learning combined with clinical parameters for precise differentiation of lipid-poor adrenal adenomas and metastases.Abdominal radiology (New York) · 2026Article
- Radiomics in Gastric Cancer: Advancing Precision Medicine.Journal of gastric cancer · 2026Review
96 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is a common disease that causes great health concerns to women worldwide. During the diagnosis and treatment of breast cancer, medical imaging plays an essential role, but its interpretation relies on radiologists or clinical doctors. Radiomics can extract high-throughput quantitative imaging features from images of various modalities via traditional machine learning or deep learning methods following a series of standard processes. Hopefully, radiomic models may aid various processes in clinical practice. In this review, we summarize the current utilization of radiomics for predicting clinicopathological indices and clinical outcomes. We also focus on radio-multi-omics studies that bridge the gap between phenotypic and microscopic scale information. Acknowledging the deficiencies that currently hinder the clinical adoption of radiomic models, we discuss the underlying causes of this situation and propose future directions for advancing radiomics in breast cancer research.
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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.