ArticleScientific reports2019
Breast-lesions characterization using Quantitative Ultrasound features of peritumoral tissue.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematized Review of Quantitative Ultrasound Based on First-Order Speckle Statistics.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2024Pooled it
- The Role of Quantitative Ultrasound in Monitoring Neoadjuvant Chemotherapy in Breast Cancer: A Narrative Review.Cancers · 2025Review
- Differentiating triple-negative breast cancer and atypical fibroadenomas using an ultrasound-based radiomics nomogram.BMC medical imaging · 2025Article
- Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer.Journal of imaging · 2025Article
- Influences of Variability in Attenuation Compensation on the Estimation of Backscatter Coefficient of Median Nerves in Vivo.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2025Article
- Evaluation of fragility fracture risk using deep learning based on ultrasound radio frequency signal.Endocrine · 2024Article
- Development of a nomogram-based model combining intra- and peritumoral ultrasound radiomics with clinical features for differentiating benign from malignant in Breast Imaging Reporting and Data System category 3-5 nodules.Quantitative imaging in medicine and surgery · 2023Article
- Breast cancer patient-derived microtumors resemble tumor heterogeneity and enable protein-based stratification and functional validation of individualized drug treatment.Journal of experimental & clinical cancer research : CR · 2023Article
- Ultrasound Characterization of Cortical Bone Using Shannon Entropy.Ultrasound in medicine & biology · 2023Article
- Texture quantified from ultrasound Nakagami parametric images is diagnostically relevant for breast tumor characterization.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Subclavian brachial plexus metastasis from breast cancer: A case report.World journal of clinical cases · 2022Article
- Cystic (including atypical) and solid breast lesion classification using the different features of quantitative ultrasound parametric images.International journal of computer assisted radiology and surgery · 2022Article
- Diagnostic performance of perilesional radiomics analysis of contrast-enhanced mammography for the differentiation of benign and malignant breast lesions.European radiology · 2022Article
- Breast Tumor Classification Using Intratumoral Quantitative Ultrasound Descriptors.Computational and mathematical methods in medicine · 2022Article
- Review
- Differential diagnosis between small breast phyllodes tumors and fibroadenomas using artificial intelligence and ultrasound data.Quantitative imaging in medicine and surgery · 2021Article
- A new CNN architecture for efficient classification of ultrasound breast tumor images with activation map clustering based prediction validation.Medical & biological engineering & computing · 2021Article
- A novel quantitative and reference-free ultrasound analysis to discriminate different concentrations of bone mineral content.Scientific reports · 2021Article
- Application of ultrasound artificial intelligence in the differential diagnosis between benign and malignant breast lesions of BI-RADS 4A.BMC cancer · 2020Article
- Comparison of methods for texture analysis of QUS parametric images in the characterization of breast lesions.PloS one · 2020Article
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5 authors.
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Abstract
The presented studies evaluate for the first time the efficiency of tumour classification based on the quantitative analysis of ultrasound data originating from the tissue surrounding the tumour. 116 patients took part in the study after qualifying for biopsy due to suspicious breast changes. The RF signals collected from the tumour and tumour-surroundings were processed to determine quantitative measures consisting of Nakagami distribution shape parameter, entropy, and texture parameters. The utility of parameters for the classification of benign and malignant lesions was assessed in relation to the results of histopathology. The best multi-parametric classifier reached an AUC of 0.92 and of 0.83 for outer and intra-tumour data, respectively. A classifier composed of two types of parameters, parameters based on signals scattered in the tumour and in the surrounding tissue, allowed the classification of breast changes with sensitivity of 93%, specificity of 88%, and AUC of 0.94. Among the 4095 multi-parameter classifiers tested, only in eight cases the result of classification based on data from the surrounding tumour tissue was worse than when using tumour data. The presented results indicate the high usefulness of QUS analysis of echoes from the tissue surrounding the tumour in the classification of breast lesions.
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