ArticleEuropean radiology2018
Automated breast volume scanner (ABVS) in assessing breast cancer size: A comparison with conventional ultrasound and magnetic resonance imaging.
Article in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 31 citations in OpenAlex.
- Deep Learning Based on Automated Breast Volume Scanner Images for the Diagnosis of Breast Lesions: A Multicenter Diagnostic Study.International journal of medical sciences · 2025Trial
- YOLO AI model based on an automated breast volume scanner for the detection of benign and malignant breast lesions.Quantitative imaging in medicine and surgery · 2025Article
- A nomogram for diagnosis of BI-RADS 4 breast nodules based on three-dimensional volume ultrasound.BMC medical imaging · 2025Article
- Integrating multimodal ultrasound imaging and machine learning for predicting luminal and non-luminal breast cancer subtypes.Frontiers in oncology · 2025Article
- Preoperative discrimination of invasive and non-invasive breast cancer using machine learning based on automated breast volume scanning (ABVS) radiomics and virtual touch quantification (VTQ).Discover oncology · 2024Article
- Ultrasonic features of automated breast volume scanner (ABVS) and handheld ultrasound (HHUS) combined with molecular biomarkers in predicting axillary lymph node metastasis of clinical T1-T2 breast cancer.Quantitative imaging in medicine and surgery · 2024Article
- Multiview deep learning networks based on automated breast volume scanner images for identifying breast cancer in BI-RADS 4.Frontiers in oncology · 2024Article
- Neoadjuvant chemotherapy for breast cancer: an evaluation of its efficacy and research progress.Frontiers in oncology · 2023Review
- Development and internal validation of a conventional ultrasound-based nomogram for predicting malignant nonmasslike breast lesions.Quantitative imaging in medicine and surgery · 2022Article
- Identification of the lymph node metastasis-related automated breast volume scanning features for predicting axillary lymph node tumor burden of invasive breast cancerFrontiers in endocrinology · 2022Article
- Microscopic Tumour Classification by Digital Mammography.Journal of healthcare engineering · 2021Article
- Preoperative assessment of breast cancer: Multireader comparison of contrast-enhanced MRI versus the combination of unenhanced MRI and digital breast tomosynthesis.Breast (Edinburgh, Scotland) · 2020Article
- Diagnostic value of an automated breast volume scanner compared with a hand-held ultrasound: a meta-analysis.Gland surgery · 2019Article
- Characteristics of contrast-enhanced ultrasonography and strain elastography of locally advanced breast cancer.Journal of thoracic disease · 2019Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo compare automated breast volume scanner (ABVS), ultrasound (US) and MRI in measuring breast cancer size, and evaluate the agreement between ABVS and US in assessing lesion location and sonographic features.
methodsWe retrospectively included 98 women with 100 index cancers who had undergone US and ABVS followed by 1.5T MRI. Images were interpreted by a pool of readers reporting lesion size, location and breast imaging reporting and data system (BI-RADS) features. Bland-Altman analysis (with logarithmic data transformation), intraclass correlation coefficient (ICC) and Cohen's kappa statistic were used for statistical analysis.
resultsMRI showed the best absolute agreement with histology in measuring cancer size (ICC 0.93), with LOA comparable to those of ABVS (0.63-1.99 vs. 0.52-1.73, respectively). Though ABVS and US had highly concordant measurements (ICC 0.95), ABVS showed better agreement with histology (LOA 0.52-1.73 vs. 0.45-1.86, respectively), corresponding to a higher ICC (0.85 vs. 0.75, respectively). Except for posterior features (k=0.39), the agreement between US and ABVS in attributing site and BI-RADS features ranged from substantial to almost perfect (k=0.68-0.85).
conclusionsABVS performs better than US and approaches MRI in predicting breast cancer size. ABVS performs comparably to US in sonographic assessment of lesions. KEY POINTS: • ABVS approaches MRI in predicting breast cancer size. • ABVS is equivalent to US in localising and characterising breast cancer. • ABVS is more accurate than US in assessing breast cancer size. • ABVS has the potential to replace US in breast cancer staging.
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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.