title: Clinical Evaluation of a 3-D Automatic Annotation Method for Breast Ultrasound Imaging.
abstract: The routine clinical breast ultrasound annotation method is limited by the time it consumes, inconsistency, inaccuracy and incomplete notation. A novel 3-D automatic annotation method for breast ultrasound imaging has been developed that uses a spatial sensor to track and record conventional B-mode scanning so as to provide more objective annotation. The aim of the study described here was to test the feasibility of the automatic annotation method in clinical breast ultrasound scanning. An ultrasound scanning procedure using the new method was established. The new method and the conventional manual annotation method were compared in 46 breast cancer patients (49 ± 12 y). The time used for scanning a patient was recorded and compared for the two methods. Intra-observer and inter-observer experiments were performed, and intra-class correlation coefficients (ICCs) were calculated to analyze system reproducibility. The results revealed that the new annotation method had an average scanning time 36 s (42.9%) less than that of the conventional method. There were high correlations between the results of the two annotation methods (r = 0.933, p < 0.0001 for distance; r = 0.995, p < 0.0001 for radial angle). Intra-observer and inter-observer reproducibility was excellent, with all ICCs > 0.92. The results indicated that the 3-D automatic annotation method is reliable for clinical breast ultrasound scanning and can greatly reduce scanning time. Although large-scale clinical studies are still needed, this work verified that the new annotation method has potential to be a valuable tool in breast ultrasound examination.
authors.affiliation: Interdisciplinary Division of Biomedical Engineering, Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
authors.forename: Wei-Wei
authors.initials: WW
authors.lastname: Jiang
authors.affiliation: Department of Ultrasound, State Key Laboratory of Oncology in Southern China, Sun Yat-Sen University Cancer Center, Guangzhou, China; Department of Ultrasound, Hospital of Traditional Chinese Medicine of Zhongshan, Zhongshan, China.
authors.forename: Cheng
authors.initials: C
authors.lastname: Li
authors.affiliation: Department of Ultrasound, State Key Laboratory of Oncology in Southern China, Sun Yat-Sen University Cancer Center, Guangzhou, China.
authors.forename: An-Hua
authors.initials: AH
authors.lastname: Li
authors.affiliation: Interdisciplinary Division of Biomedical Engineering, Hong Kong Polytechnic University, Kowloon, Hong Kong, China. Electronic address: ypzheng@ieee.org.
authors.forename: Yong-Ping
authors.initials: YP
authors.lastname: Zheng
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D004282:Documentation / Q000379:methods; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D000069550:Machine Learning; D008875:Middle Aged; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D011873:Radiology Information Systems / Q000458:organization & administration*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016217:Ultrasonography, Mammary / Q000379:methods*
keywords: 3-D ultrasound; Annotation; Breast cancer; Breast imaging; Breast ultrasound; Clinical study