SynthesisLa Radiologia medica2024
Ultrasound-based radiomics for early predicting response to neoadjuvant chemotherapy in patients with breast cancer: a systematic review with meta-analysis.
Synthesis in La Radiologia medica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Ultrasound-based predictive models for response to neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis.BMC cancer · 2026Pooled it
- Quality and accuracy of radiomics models in predicting KRAS status in lung cancer: a systematic review and meta-analysis.Frontiers in oncology · 2025Pooled it
- Machine learning model for the prediction of pathological complete response after neoadjuvant chemotherapy in breast cancer.BMC cancer · 2026Article
- B-Mode Ultrasound Radiomics for Differentiating Benign and Malignant Small Hyperechoic Renal Masses: An Exploratory Single-Center Experience.Journal of imaging · 2026Article
- MBUCF: a cross-fusion method for multimodal breast ultrasound based on multidimensional features.Quantitative imaging in medicine and surgery · 2026Article
- Deep learning 3D super-resolution radiomics model based on Gd-enhanced MRI for improving preoperative prediction of HCC pathological grading.Abdominal radiology (New York) · 2026Article
- Quantitative Ultrasound Radiomics for Predicting and Monitoring Neoadjuvant Chemotherapy Response in Breast Cancer: A Systematic Review.Diagnostics (Basel, Switzerland) · 2026Review
- Predicting pathological complete response to breast cancer neoadjuvant therapy using multi-combination machine learning models based on vision transformer features.Scientific reports · 2025Article
- Prediction of neoadjuvant chemotherapy efficacy in patients with HER2-low breast cancer based on ultrasound radiomics.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Review
- Enhanced HER-2 prediction in breast cancer through synergistic integration of deep learning, ultrasound radiomics, and clinical data.Scientific reports · 2025Article
- Integrative multimodal ultrasound and radiomics for early prediction of neoadjuvant therapy response in breast cancer: a clinical study.BMC cancer · 2025Article
- Ultrasound-based radiomics and machine learning for enhanced diagnosis of knee osteoarthritis: Evaluation of diagnostic accuracy, sensitivity, specificity, and predictive value.European journal of radiology open · 2025Article
- Article
- Nomogram Development for Assessing Oncotype DX Recurrence Scores in Breast Cancer: A Chinese Population Study.Cancer medicine · 2025Article
- Combination of ultrasound-based radiomics and deep learning with clinical data to predict response in breast cancer patients treated with neoadjuvant chemotherapy.Frontiers in oncology · 2025Article
- Personalized predictions of neoadjuvant chemotherapy response in breast cancer using machine learning and full-field digital mammography radiomics.Frontiers in medicine · 2025Article
- An Update of AI and Radiomics in Precision Oncology: Insights from Liver Tumors as Case Models.Technology in cancer research & treatmentReview
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveThis study aims to evaluate the diagnostic accuracy of ultrasound imaging (US)-based radiomics for the early prediction of response to neoadjuvant chemotherapy (NAC) in breast cancer patients.
methodsWe comprehensively searched PubMed, Cochrane Library, Embase, and Web of Science databases up to 1 January 2023 for eligible studies. We assessed the methodological quality of the enrolled studies with Radiomics Quality Score (RQS) and the Quality Assessment of Diagnostic Accuracy Studies-2 tools. We performed meta-analyses to summarize the diagnostic efficacy of US-based radiomics in response to NAC in breast cancer patients.
resultsEight studies proved eligible. Eligible studies exhibited an average RQS score of 12.88 (35.8% of the total score), with the RQS score ranging from 8 to 19. In the meta-analyses, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.87 (95% CI 0.81-0.92), 0.78 (95% CI 0.72-0.83), 4.02 (95% CI 3.18-5.08), 0.16 (95% CI 0.10-0.25), and 25.17 (95% CI 15.10-41.95), respectively. Results from subgroup analyses indicated that prospective studies apparently exhibited more optimal sensitivity than retrospective studies. Sensitivity analyses exhibited similar results to the primary analyses.
conclusionUS-based radiomics may be a potentially crucial adjuvant method for evaluating the response of breast cancer to NAC. Due to limited data available and low quality of eligible studies, more multicenter prospective studies with rigorous methods are required to confirm our findings.
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