title: Clinical value of radiofrequency ultrasonic local estimators in classifying breast lesions.
abstract: OBJECTIVE
  We sought to summarize the features of radiofrequency ultrasonic local estimator (RULES) images of benign and malignant masses and to explore the diagnostic value of RULES scores to identify breast lumps.
  
  
  METHODS
  A total of 81 women with a mean age ± SD of 41.33 ± 12.03 years (range, 19-68 years) with 82 lesions seen at our hospital were included in this study. Inclusion criteria were Breast Imaging Reporting and Data System grade 2 to 5 breast lesions, preoperative 2-dimensional (2D) ultrasound (US) examinations and RULES image acquisition, no treatment before the US examinations, surgical resection in our hospital, and histopathologic results. Each RULES characteristic was scored on the basis of expected values for malignant characteristics, and this RULES scoring system was assessed by a receiver operating characteristic curve.
  
  
  RESULTS
  Of the 82 lesions, 45 were benign, and 37 were malignant. Malignancy was associated with multiple colors, red as the main color, colors distributed in 3 or more locations, aggregated colors, and more than half of the area filled with colors. A RULES score of 7 had the highest sum of sensitivity (67.6%) and specificity (95.6%) and the highest accuracy (82.9%) for diagnosis of malignancy. When 2D US imaging a Breast Imaging Reporting and Data System category of 4 was combined with a RULES score of 4 to detect breast cancer, the sensitivity was 83.8%; the specificity was 93.3%; and the accuracy increased to 89.0%.
  
  
  CONCLUSIONS
  The use of RULES images and characteristics is helpful in differentiating benign and malignant breast lesions. Diagnostic accuracy can be improved by combining 2D US imaging and RULES.
authors.affiliation: Department of Ultrasound, Shanxi Academy of Medical Sciences and Shanxi Dayi Hospital, 99 Longcheng Da Jie, 030032 Taiyuan, Shanxi, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Wang
authors.forename: Chunsong
authors.initials: C
authors.lastname: Kang
authors.forename: Xiaofang
authors.initials: X
authors.lastname: Liu
authors.forename: Tingting
authors.initials: T
authors.lastname: Li
authors.forename: Yu
authors.initials: Y
authors.lastname: Wang
authors.forename: Tinghua
authors.initials: T
authors.lastname: Feng
authors.forename: Zhaojun
authors.initials: Z
authors.lastname: Li
authors.forename: Jiping
authors.initials: J
authors.lastname: Xue
authors.forename: Kailing
authors.initials: K
authors.lastname: Shi
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology / Q000601:surgery; D016009:Chi-Square Distribution; D005260:Female; D006801:Humans; D008875:Middle Aged; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric; D018615:Ultrasonography, Doppler, Color; D016217:Ultrasonography, Mammary / Q000379:methods*