Benign breast lesions: Ultrasound.
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ABSTRACT:
SUBMITTER: Masciadri N
PROVIDER: S-EPMC3558101 | biostudies-literature | 2011 Jun
REPOSITORIES: biostudies-literature
Publications
Benign breast diseases constitute a heterogeneous group of lesions arising in the mammary epithelium or in other mammary tissues, and they may also be linked to vascular, inflammatory or traumatic pathologies. Most lesions found in women consulting a physician are benign. Ultrasound (US) diagnostic criteria indicating a benign lesion are described as well as US findings in the most frequent benign breast lesions. ...[more]
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Project description:ObjectivesThe aim of this study was to evaluate breast multiparametric ultrasound (mpUS) and its potential to reduce unnecessary breast biopsies with 1, 2, or 3 additional quantitative parameters (Doppler, elastography, and contrast-enhanced ultrasound [CEUS]) to B-mode and investigate possible variations with different reader experience.Materials and methodsThis prospective study included 124 women (age range, 18-82 years; mean, 52 years), each with 1 new breast lesion, scheduled for ultrasound-guided biopsy between October 2015 and September 2016. Each lesion was examined with B-mode, elastography (Virtual Touch IQ [VTIQ]), Doppler, and CEUS, and different quantitative parameters were recorded for each modality. Four readers (2 experienced breast radiologists and 2 in-training) independently evaluated B-mode images of each lesion and assigned a BI-RADS (Breast Imaging Reporting and Data System) score. Using the area under the receiver operating characteristic curve (AUC), the most accurate quantitative parameter for each modality was chosen. These were then combined with the BI-RADS scores of all readers. Descriptive statistics and AUC were used to evaluate the diagnostic performance of mpUS.ResultsSixty-five lesions were malignant. MpUS with B-mode and 2 additional quantitative parameters (VTIQ and CEUS or Doppler) showed the highest diagnostic performance for all readers (averaged AUCs, 0.812-0.789 respectively vs 0.683 for B-mode, P = 0.0001). Both combinations significantly reduced the number of false-positive findings up to 46.9% (P < 0.0001).ConclusionsQuantitative mpUS with 2 different triple assessment modalities (B-mode, VTIQ elastography, CEUS, or Doppler) shows the best diagnostic performance for breast cancer diagnosis and leads to a significant reduction of false-positive biopsy recommendations, for both experienced and inexperienced readers.
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Project description:The aim of the present study was to assess the performance of contrast-enhanced ultrasound in distinguishing between malignant and benign breast lesions and the diagnostic value of its clinical application. A total of 52 cases with malignant breast tumors and 73 cases with benign breast lesions were included in the study. Time-intensity curves (TICs) for contrast-enhanced ultrasound were recorded, and the perfusion parameters were obtained and analyzed. Typical features of malignant breast tumors included irregular shape and vascular morphology, uneven contrast agent distribution, filling defects and contrast agent retention, 'fast-out' wash-out mode, unclear boundaries and uneven internal echo. Benign lesions were characterized by 'slow-out' or synchronous wash-out mode. Regarding perfusion, the starting time of the perfusion of the Sone-Vue microbubble contrast (always 20-30 sec) and time to peak (TTP) were significantly earlier for the malignant lesions, while the wash-out time was later. A significantly greater peak intensity, rising slope and area under the TIC were observed for the malignant breast lesions. All of the malignant breast lesions exhibited an enlarged focus scope on ultrasound, while no obvious focus scope enhancement was observed for benign breast lesions. Furthermore, the TICs of 88.4% of malignant breast lesions were of the fast-rising and slow-declining type, while the TICs of 75.3 and 17.8% of the benign breast lesions were of the slow-rising and fast-declining, and fast-rising and fast-declining type, respectively. Receiver operating characteristics analysis indicated that the TTP, wash-out time and rising slope might contribute to the differential diagnosis between malignant and benign breast lesions. In conclusion, TIC parameters of contrast-enhanced ultrasound have promising clinical value in differentiating between malignant and benign breast lesions. The TTP, wash-out time and rising slope may contribute to the diagnosis of patients with breast lesions to facilitate timely treatment and prognostication of breast cancer patients.
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Project description:PurposeThis study aimed to establish and evaluate the usefulness of a simple, practical, and easy-to-promote machine learning model based on ultrasound imaging features for diagnosing breast cancer (BC).Materials and methodsLogistic regression, random forest, extra trees, support vector, multilayer perceptron, and XG Boost models were developed. The modeling data set of 1345 cases was from a tertiary class A hospital in China. The external validation data set of 1965 cases were from 3 tertiary class A hospitals and 2 primary hospitals. The area under the receiver operating characteristic curve (AUC) was used as the main evaluation index, and pathological biopsy was used as the gold standard for evaluating each model. Diagnostic capability was also compared with that of clinicians.ResultsAmong the six models, the logistic model showed superior diagnostic efficiency, with an AUC of 0.771 and 0.906 and Brier scores of 0.181 and 0.165 in the test and validation sets, respectively. The AUCs of the clinician diagnosis and the logistic model were 0.913 and 0.906. Their AUCs in the tertiary class A hospitals were 0.915 and 0.915, respectively, and were 0.894 and 0.873 in primary hospitals, respectively.ConclusionThe externally validated logical model can be used to distinguish between malignant and benign breast lesions in ultrasound images. Compared with clinician diagnosis, the logistic model has better diagnostic efficiency, making it potentially useful to assist in screening, particularly in lower level medical institutions.Trial registrationhttp://www.clinicaltrials.gov. ClinicalTrials.gov ID: NCT03080623.
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Project description:BackgroundConventional ultrasound (CUS) is the first choice for discrimination benign and malignant lymphadenectasis in supraclavicular lymph nodes (SCLNs), which is important for the further treatment. Radiomics provide more comprehensive and richer information than radiographic images, which are imperceptible to human eyes.ObjectiveThis study aimed to explore the clinical value of CUS-based radiomics analysis in preoperative differentiation of malignant from benign lymphadenectasis in CUS suspected SCLNs.MethodsThe characteristics of CUS images of 189 SCLNs were retrospectively analyzed, including 139 pathologically confirmed benign SCLNs and 50 malignant SCLNs. The data were randomly divided (7:3) into a training set (n=131) and a validation set (n=58). A total of 744 radiomics features were extracted from CUS images, radiomics score (Rad-score) built were using least absolute shrinkage and selection operator (LASSO) logistic regression. Rad-score model, CUS model, radiomics-CUS (Rad-score + CUS) model, clinic-radiomics (Clin + Rad-score) model, and combined CUS-clinic-radiomics (Clin + CUS + Rad-score) model were built using logistic regression. Diagnostic accuracy was assessed by receiver operating characteristic (ROC) curve analysis.ResultsA total of 20 radiomics features were selected from 744 radiomics features and calculated to construct Rad-score. The AUCs of Rad-score model, CUS model, Clin + Rad-score model, Rad-score + CUS model, and Clin + CUS + Rad-score model were 0.80, 0.72, 0.85, 0.83, 0.86 in the training set and 0.77, 0.80, 0.82, 0.81, 0.85 in the validation set. There was no statistical significance among the AUC of all models in the training and validation set. The calibration curve also indicated the good predictive performance of the proposed nomogram.ConclusionsThe Rad-score model, derived from supraclavicular ultrasound images, showed good predictive effect in differentiating benign from malignant lesions in patients with suspected supraclavicular lymphadenectasis.
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