Literature DB >> 32185702

S-Detect characterization of focal breast lesions according to the US BI RADS lexicon: a pictorial essay.

Tommaso Vincenzo Bartolotta1,2, Alessia Angela Maria Orlando3, Luigi Spatafora1, Mariangela Dimarco1, Cesare Gagliardo1, Adele Taibbi1.   

Abstract

High-resolution ultrasonography (US) is a valuable tool in breast imaging. Nevertheless, US is an operator-dependent technique: to overcome this issue, the American College of Radiology (ACR) has developed the breast imaging-reporting and data system (BI-RADS) US lexicon. Despite this effort, the variability in the assessment of focal breast lesions (FBLs) with the use of BI-RADS US lexicon is still an issue. Within this framework, evidence shows that computer-aided image analysis may be effective in improving the radiologist's assessment of FBLs. In particular, S-Detect is a newly developed image-analytic computer program that provides assistance in morphologic analysis of FBLs seen on US according to the BI-RADS US lexicon. This pictorial essay describes state-of-the-art of sonographic characterization of FBLs by using S-Detect.

Entities:  

Keywords:  BI-RADS; Breast neoplasms; Computer-assisted diagnosis; Decision-making; Problem-solving; Ultrasonography

Mesh:

Year:  2020        PMID: 32185702      PMCID: PMC7242582          DOI: 10.1007/s40477-020-00447-w

Source DB:  PubMed          Journal:  J Ultrasound        ISSN: 1876-7931


  16 in total

1.  BI-RADS for sonography: positive and negative predictive values of sonographic features.

Authors:  Andrea S Hong; Eric L Rosen; Mary S Soo; Jay A Baker
Journal:  AJR Am J Roentgenol       Date:  2005-04       Impact factor: 3.959

2.  Characterisation of indeterminate focal breast lesions on grey-scale ultrasound: role of ultrasound elastography.

Authors:  T V Bartolotta; R Ienzi; A Cirino; C Genova; F Ienzi; D Pitarresi; E Safina; M Midiri
Journal:  Radiol Med       Date:  2011-03-07       Impact factor: 3.469

3.  Ultrasound-guided preoperative localization of breast lesions: a good choice.

Authors:  Giorgio Carlino; Pierluigi Rinaldi; Michela Giuliani; Rossella Rella; Enida Bufi; Federico Padovano; Chiara Ciardi; Maurizio Romani; Paolo Belli; Riccardo Manfredi
Journal:  J Ultrasound       Date:  2018-10-26

4.  Focal breast lesion characterization according to the BI-RADS US lexicon: role of a computer-aided decision-making support.

Authors:  Tommaso Vincenzo Bartolotta; Alessia Orlando; Vito Cantisani; Domenica Matranga; Raffele Ienzi; Alessandra Cirino; Francesco Amato; Maria Laura Di Vittorio; Massimo Midiri; Roberto Lagalla
Journal:  Radiol Med       Date:  2018-03-22       Impact factor: 3.469

5.  Automated classification of focal breast lesions according to S-detect: validation and role as a clinical and teaching tool.

Authors:  Mattia Di Segni; Valeria de Soccio; Vito Cantisani; Giacomo Bonito; Antonello Rubini; Gabriele Di Segni; Sveva Lamorte; Valentina Magri; Corrado De Vito; Giuseppe Migliara; Tommaso Vincenzo Bartolotta; Alessio Metere; Laura Giacomelli; Carlo de Felice; Ferdinando D'Ambrosio
Journal:  J Ultrasound       Date:  2018-04-21

Review 6.  Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review.

Authors:  Afsaneh Jalalian; Syamsiah B T Mashohor; Hajjah Rozi Mahmud; M Iqbal B Saripan; Abdul Rahman B Ramli; Babak Karasfi
Journal:  Clin Imaging       Date:  2012-11-13       Impact factor: 1.605

Review 7.  Breast ultrasonography: state of the art.

Authors:  Regina J Hooley; Leslie M Scoutt; Liane E Philpotts
Journal:  Radiology       Date:  2013-09       Impact factor: 11.105

8.  Variability in Observer Performance Between Faculty Members and Residents Using Breast Imaging Reporting and Data System (BI-RADS)-Ultrasound, Fifth Edition (2013).

Authors:  Youn Joo Lee; So Young Choi; Kyu Sun Kim; Po Song Yang
Journal:  Iran J Radiol       Date:  2016-01-09       Impact factor: 0.212

9.  A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of breast masses on ultrasound: Added value for the inexperienced breast radiologist.

Authors:  Hee Jeong Park; Sun Mi Kim; Bo La Yun; Mijung Jang; Bohyoung Kim; Ja Yoon Jang; Jong Yoon Lee; Soo Hyun Lee
Journal:  Medicine (Baltimore)       Date:  2019-01       Impact factor: 1.817

10.  Clinical application of S-Detect to breast masses on ultrasonography: a study evaluating the diagnostic performance and agreement with a dedicated breast radiologist.

Authors:  Kiwook Kim; Mi Kyung Song; Eun-Kyung Kim; Jung Hyun Yoon
Journal:  Ultrasonography       Date:  2016-04-14
View more
  3 in total

Review 1.  Methods for the segmentation and classification of breast ultrasound images: a review.

Authors:  Ademola E Ilesanmi; Utairat Chaumrattanakul; Stanislav S Makhanov
Journal:  J Ultrasound       Date:  2021-01-11

Review 2.  Contrast-enhanced ultrasound features of breast capillary hemangioma: a case report and review of literature.

Authors:  Chen-Pin Chou; Jer-Shyung Huang; Jyh-Seng Wang; Huay-Ben Pan
Journal:  J Ultrasound       Date:  2021-01-06

3.  S-Detect characterization of focal solid breast lesions: a prospective analysis of inter-reader agreement for US BI-RADS descriptors.

Authors:  Tommaso Vincenzo Bartolotta; Alessia Angela Maria Orlando; Maria Laura Di Vittorio; Francesco Amato; Mariangela Dimarco; Domenica Matranga; Raffaele Ienzi
Journal:  J Ultrasound       Date:  2020-05-23
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.