ArticleBritish journal of cancer2024
Whole tumour- and subregion-based radiomics of contrast-enhanced mammography in differentiating HER2 expression status of invasive breast cancers: A double-centre pilot study.
Article in British journal of cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Interpretable habitat radiomics based nomogram for predicting T790M mutation in non-small cell lung cancer with brain metastases.Quantitative imaging in medicine and surgery · 2026Article
- PET/CT-based quantification of intratumoral heterogeneity for predicting pathological complete response in breast cancer patients treated with neoadjuvant chemotherapy: A multicentre study.European journal of nuclear medicine and molecular imaging · 2026Article
- MRI-based habitat and peritumoral radiomics for predicting HER2 status in breast cancer: a multicenter study.Scientific reports · 2026Article
- Non-Invasive Breast Cancer Receptor Typing from Mammograms Using Artificial Intelligence: A Systematic Review and Meta-Analysis.Journal of imaging informatics in medicine · 2026Review
- Habitat Radiomics Predict HPV Status in Oropharyngeal Cancer.Cancer medicine · 2025Article
- Advancing radiomics from contrast-enhanced mammography in breast cancer.British journal of cancer · 2025Article
- CT-based habitat radiomics for preoperative differentiation of adenocarcinoma in situ/minimally invasive adenocarcinoma from invasive adenocarcinoma manifesting as ground-glass nodules: a multicenter study.Frontiers in oncology · 2025Article
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16 authors.
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Abstract
objectivesTo explore the value of whole tumour- and subregion-based radiomics of contrast-enhanced mammography (CEM) in differentiating the HER2 expression status of breast cancers.
methods352 patients underwent preoperative CEM from two centres were consecutively enroled and divided into the training, internal validation, and external validation cohorts. The lesions were divided into HER2-positive and HER2-negative groups. Besides the radiological features, radiomics features capturing the whole tumour-based (wITH) and subregion-based intratumoral heterogeneity (sITH) were extracted from the craniocaudal view of CEM recombined images. The XGBoost classifier was applied to develop the radiological, sITH, and wITH models. A combined model was constructed by fusing the prediction results of the three models.
resultsThe mean age of the patients was 51.1 ± 10.7 years. Two radiological features, four wITH features, and three sITH features were selected to establish the models. The combined model significantly improved the AUC to 0.80 ± 0.03 (95% CI: 0.73-0.86), 0.79 ± 0.06 (95% CI: 0.67-0.90), and 0.79 ± 0.05 (95% CI: 0.69-0.89) in the training, internal validation, and external validation cohorts, respectively (All P < 0.05). The combined model showed good agreement between the predicted and observed probabilities and favourable net clinical benefit in the validation cohorts.
conclusionsBoth whole tumour- and subregion-based ITH radiomics features of CEM exhibited potential for differentiating the HER2 expression status. Combining conventional radiological features and ITH features can improve the model's performance.
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