Rossano Girometti1, Martina Zanotel2, Viviana Londero1, Anna Linda1, Michele Lorenzon1, Chiara Zuiani1. 1. Institute of Radiology, Department of Medicine, University of Udine, Azienda Sanitaria Universitaria Integrata di Udine, p.le S. Maria della Misericordia 15, 33100, Udine, Italy. 2. Institute of Radiology, Department of Medicine, University of Udine, Azienda Sanitaria Universitaria Integrata di Udine, p.le S. Maria della Misericordia 15, 33100, Udine, Italy. martina.zanotel@gmail.com.
Abstract
OBJECTIVES: To 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. METHODS: We 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. RESULTS: MRI 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). CONCLUSIONS: ABVS 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.
OBJECTIVES: To 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. METHODS: We 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. RESULTS: MRI 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). CONCLUSIONS: ABVS 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.
Entities:
Keywords:
Automated breast volume scanner; Breast cancer; Breast cancer size; Magnetic resonance imaging; Ultrasonography
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