Identification of a correlation between the sonographic appearance and molecular subtype of invasive breast cancer: A review of 311 cases

Wu, Tong; Li, Jing; Wang, Dongmo; Leng, Xiaoping; Zhang, Lei; Li, Ziyao; Jing, Hui; Kang, Jia; Tian, Jiawei

doi:10.1016/j.clinimag.2018.10.020

Cited by 25 publications

(35 citation statements)

References 35 publications

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“…In the literature, it was reported that the tumor size, patient age, and nodal status were significantly associated with the biological characteristics of tumors . For instance, a tumor size larger than 2 cm was more common in human epidermal growth factor receptor 2 and triple‐negative subtypes of IBC; patients younger than 50 years showed more hormone receptor–negative cancers compared with older patients; and nodal metastases were more frequent in patients with the human epidermal growth factor receptor 2 subtype . Therefore, when evaluating the biological properties of tumors, these preoperative clinical parameters should be taken into consideration.…”

Section: Discussionmentioning

confidence: 99%

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

Tong

Sun

Zhou

et al. 2019

J of Ultrasound Medicine

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Objectives-To investigate the value of ultrasound (US) feature-based models in predicting the proliferation and invasiveness of invasive breast cancer (IBC) and to compare the performance of models based solely on US features with models that combined US features, patient age, tumor size, and axilla status from US.Methods-With ethical approval, 746 patients with a pathologic diagnosis of IBC were reviewed for preoperative clinical, US, and postoperative pathologic data. The proliferation and invasiveness properties of the IBC included the histologic grade and Ki-67 status and lymphovascular invasion (LVI) and axillary lymph node metastasis (ALNM), respectively. Logistic regression analyses were used to identify independent risk factors for tumor proliferation and invasiveness.Results-Posterior echo enhancement, calcification, a tumor size larger than 2 cm, and suspicion of ALNM from axillary US were independent risk factors for a high histologic grade and high Ki-67 expression of IBC (P < .05). A posterior echo shadow, patient age younger than 45 years, and suspicious findings on axillary US imaging were independent variables for predicting the presence of LVI and ALNM in IBC (P < .05). Calcification was the independent factor for predicting LVI (P = .013). The predictive performance of the combined models was improved compared with the US feature-based models, with a higher accuracy rate and negative predictive value. The area under curve of the combined models was also significantly higher than that of the single models (P < .05).Conclusions-Compared with the US feature-based models, the combined models yielded better predictive performance. This may provide a more robust model to predict the tumor biological properties of IBC before surgery.

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Section: Discussionmentioning

confidence: 99%

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

Tong

Sun

Zhou

et al. 2019

J of Ultrasound Medicine

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“…In addition to the differentiation of benign and malignant breast tumors from ultrasound images, previous studies have focused on the correlation between imaging features and molecular subtypes. Breast cancers with the triple-negative subtype were more likely to be associated with circumscribed margins and were less associated with calcifications (15)(16)(17)(18). Human epidermal growth factor receptor 2 (HER2) (+) breast cancers usually show enhanced posterior acoustics on ultrasound images (15,17).…”

Section: Introductionmentioning

confidence: 99%

“…Breast cancers with the triple-negative subtype were more likely to be associated with circumscribed margins and were less associated with calcifications (15)(16)(17)(18). Human epidermal growth factor receptor 2 (HER2) (+) breast cancers usually show enhanced posterior acoustics on ultrasound images (15,17). Tumors with posterior shadowing are often found in hormone receptor (HR) (+) HER2 (-) breast cancers (16,19,20).…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Accuracy of Breast Cancer and Molecular Subtype Diagnosis by Ultrasound Image Deep Learning Model

Zhang

Wang

et al. 2021

Front. Oncol.

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Background: Breast ultrasound is the first choice for breast tumor diagnosis in China, but the Breast Imaging Reporting and Data System (BI-RADS) categorization routinely used in the clinic often leads to unnecessary biopsy. Radiologists have no ability to predict molecular subtypes with important pathological information that can guide clinical treatment.Materials and Methods: This retrospective study collected breast ultrasound images from two hospitals and formed training, test and external test sets after strict selection, which included 2,822, 707, and 210 ultrasound images, respectively. An optimized deep learning model (DLM) was constructed with the training set, and the performance was verified in both the test set and the external test set. Diagnostic results were compared with the BI-RADS categorization determined by radiologists. We divided breast cancer into different molecular subtypes according to hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression. The ability to predict molecular subtypes using the DLM was confirmed in the test set.Results: In the test set, with pathological results as the gold standard, the accuracy, sensitivity and specificity were 85.6, 98.7, and 63.1%, respectively, according to the BI-RADS categorization. The same set achieved an accuracy, sensitivity, and specificity of 89.7, 91.3, and 86.9%, respectively, when using the DLM. For the test set, the area under the curve (AUC) was 0.96. For the external test set, the AUC was 0.90. The diagnostic accuracy was 92.86% with the DLM in BI-RADS 4a patients. Approximately 70.76% of the cases were judged as benign tumors. Unnecessary biopsy was theoretically reduced by 67.86%. However, the false negative rate was 10.4%. A good prediction effect was shown for the molecular subtypes of breast cancer with the DLM. The AUC were 0.864, 0.811, and 0.837 for the triple-negative subtype, HER2 (+) subtype and HR (+) subtype predictions, respectively.Conclusion: This study showed that the DLM was highly accurate in recognizing breast tumors from ultrasound images. Thus, the DLM can greatly reduce the incidence of unnecessary biopsy, especially for patients with BI-RADS 4a. In addition, the predictive ability of this model for molecular subtypes was satisfactory,which has specific clinical application value.

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“…However, the primary limitation of ultrasound as a means of radiogenomics analysis is that image acquisition is highly user-dependent which hampers retrospective datasets. US is consequently the least studied modality for radiogenomics (25)(26)(27)(28)(29). To improve image reproducibility, images from automatic breast ultrasound images can be analyzed such as in the work by Zheng et al (27).…”

Section: Usmentioning

confidence: 99%

“…These imaging variables must be well-defined to limit inter-or intraobserver variability and therefore features used in clinical practice such as the BI-RADS descriptors are often used (40). For example, Wu et al found that HER2-enriched molecular subtype breast cancers were associated with the BI-RADS ultrasound margin descriptors of indistinct and spiculated (26). Human identified features offer the potential advantage of being easier to adopt into clinical practice, but the scope of potential features is limited and even the most well-defined features have notable inter-observer variability (41,42).…”

Section: Image Analysis Imaging Featuresmentioning

confidence: 99%

Breast Cancer Radiogenomics: Current Status and Future Directions

Grimm

Mazurowski

2020

Academic Radiology

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Identification of a correlation between the sonographic appearance and molecular subtype of invasive breast cancer: A review of 311 cases

Cited by 25 publications

References 35 publications

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

Evaluating the Accuracy of Breast Cancer and Molecular Subtype Diagnosis by Ultrasound Image Deep Learning Model

Breast Cancer Radiogenomics: Current Status and Future Directions

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