Inter-rater reliability and double reading analysis of an automated three-dimensional breast ultrasound system: comparison of two independent examiners
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Abstract
PURPOSE: Breast ultrasound could be a valuable tool complementary to mammography in breast cancer screening. Automated 3D breast ultrasound (ABUS) addresses challenges of hand-held ultrasound and could allow double reading analysis of ultrasound images. This trial assesses the inter-rater reliability and double reading analysis of an ABUS system.
METHODS: To assess the reproducibility and diagnostic validity of the ABUS system, SomoV™, a blinded double reading analysis, was performed in 1019 patients (2038 breasts) by two examiners (examiner A/B) and compared to single reading results, as well as to the reference standard regarding its diagnostic validity. Cohen's kappa coefficients were calculated to measure the inter-rater reliability and agreement of the different diagnostic modalities. Patient comfort and time consumption for image acquisition and reading were analyzed descriptively as secondary objectives.
RESULTS: Analysis of inter-rater reliability yielded agreement in 81.6% (κ = 0.37; p < 0.0001) showing fair agreement. Single reading analysis of SomoV™ exams (examiner A/examiner B) compared to reference standard showed good specificity (examiner A: 88.3%/examiner B: 84.5%), fair inter-rater agreement (examiner A: κ = 0.31/examiner B: κ = 0.31), and adequate sensitivity (examiner A: 53.1%/examiner B: 64.2%). Double reading analysis yielded good sensitivity and specificity (73.7 and 77.7%). Mammography (n = 1911) alone detected 160 of 176 carcinomas (sensitivity 90.1%). Adding SomoV™ to mammography would have detected 12 additional carcinomas, resulting in a higher sensitivity of 97.7%.
CONCLUSION: SomoV™ is a promising technique with good sensitivity, high patient comfort, and fair inter-examiner reliability. It allows double reading analysis that, in combination with mammography, could increase detection rates in breast cancer screening.
Bibliographical data
Original language | English |
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ISSN | 0932-0067 |
DOIs | |
Publication status | Published - 09.2017 |
PubMed | 28748340 |
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