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J Ultrasound. 2018 Jun;21(2):105-118. doi: 10.1007/s40477-018-0297-2. Epub 2018 Apr 21.

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

Author information

1
U.O.C. Diagnostica per Immagini, P. O San Paolo - ASL Roma 4, Largo dei Donatori del Sangue 1, 00053, Civitavecchia (RM), Italy. mattia.di.segni@gmail.com.
2
U.O.C. Diagnostica per Immagini, P. O San Paolo - ASL Roma 4, Largo dei Donatori del Sangue 1, 00053, Civitavecchia (RM), Italy.
3
Arakne S.r.l., Via Edoardo d'Onofrio, 304, 00155, Rome, RM, Italy.
4
Department of Public Health and Infectious Diseases, Sapienza University of Rome, Piazzale Aldo Moro 5, Rome, Italy.
5
Department of Radiology, University of Palermo, 90127, Palermo, Italy.
6
Department of Surgical Sciences, Sapienza University of Rome, viale del Policlinico 155, 00161, Rome, Italy.

Abstract

PURPOSE:

To assess the diagnostic performance and the potential as a teaching tool of S-detect in the assessment of focal breast lesions.

METHODS:

61 patients (age 21-84 years) with benign breast lesions in follow-up or candidate to pathological sampling or with suspicious lesions candidate to biopsy were enrolled. The study was based on a prospective and on a retrospective phase. In the prospective phase, after completion of baseline US by an experienced breast radiologist and S-detect assessment, 5 operators with different experience and dedication to breast radiology performed elastographic exams. In the retrospective phase, the 5 operators performed a retrospective assessment and categorized lesions with BI-RADS 2013 lexicon. Integration of S-detect to in-training operators evaluations was performed by giving priority to S-detect analysis in case of disagreement. 2 × 2 contingency tables and ROC analysis were used to assess the diagnostic performances; inter-rater agreement was measured with Cohen's k; Bonferroni's test was used to compare performances. A significance threshold of p = 0.05 was adopted.

RESULTS:

All operators showed sensitivity > 90% and varying specificity (50-75%); S-detect showed sensitivity > 90 and 70.8% specificity, with inter-rater agreement ranging from moderate to good. Lower specificities were improved by the addition of S-detect. The addition of elastography did not lead to any improvement of the diagnostic performance.

CONCLUSIONS:

S-detect is a feasible tool for the characterization of breast lesions; it has a potential as a teaching tool for the less experienced operators.

KEYWORDS:

Breast lesion characterization; Breast tumors; CAD; S-detect; US-elastography

PMID:
29681007
PMCID:
PMC5972107
DOI:
10.1007/s40477-018-0297-2
[Indexed for MEDLINE]
Free PMC Article

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