Predicting Molecular Subtypes of Breast Cancer with Mammography and Ultrasound Findings: Introduction of Sono-Mammometry Score

Shaikh, Sana; Rasheed, Afshan Asghar

doi:10.1155/2021/6691958

Cited by 6 publications

(6 citation statements)

References 23 publications

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“…Logistic regression analysis showed that Basal-like breast cancer was mostly characterized by regular shape, circumscribed margins and abnormal lymph nodes ( P <0.05). This is supported by previous studies ( 32 – 34 ). This may be due to the high degree of malignancy of Basal-like breast cancer, relatively fast growth, tumor cell growth in the marginal zone, and less connective tissue response ( 24 ).…”

Section: Discussionsupporting

confidence: 93%

Association between ultrasound BI-RADS signs and molecular typing of invasive breast cancer

et al. 2023

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ObjectiveTo explore the correlation between ultrasound images and molecular typing of invasive breast cancer, so as to analyze the predictive value of preoperative ultrasound for invasive breast cancer.Methods302 invasive breast cancer patients were enrolled in Heping Hospital affiliated to Changzhi Medical College in Shanxi, China during 2020 to 2022. All patients accepted ultrasonic and pathological examination, and all pathological tissues received molecular typing with immunohistochemical (IHC) staining. The relevance between different molecular typings and ultrasonic image, pathology were evaluated.ResultsUnivariate analysis: among the four molecular typings, there were significant differences in tumor size, shape, margin, lymph node and histological grade (P<0.05). 1. Size: Luminal A tumor was smaller (69.4%), Basal -like type tumors are mostly larger (60.9%); 2. Shape: Basal-like type is more likely to show regular shape (45.7%); 3. Margin: Luminal A and Luminal B mostly are not circumscribed (79.6%, 74.8%), Basal -like type shows circumscribed(52.2%); 4. Lymph nodes: Luminal A type tends to be normal (87.8%), Luminal B type,Her-2+ type and Basal-like type tend to be abnormal (35.6%,36.4% and 39.1%). There was no significant difference in mass orientation, echo pattern, rear echo and calcification (P>0.05). Multivariate analysis: Basal-like breast cancer mostly showed regular shape, circumscribed margin and abnormal lymph nodes (P<0.05).ConclusionThere are differences in the ultrasound manifestations of different molecular typings of breast cancer, and ultrasound features can be used as a potential imaging index to provide important information for the precise diagnosis and treatment of breast cancer.

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Section: Discussionsupporting

confidence: 93%

Association between ultrasound BI-RADS signs and molecular typing of invasive breast cancer

et al. 2023

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“…The angular/spiculated margin and posterior acoustic attenuation are well-known typical sonographic features of malignant breast tumors. The angular/spiculated margin is believed to be associated with the low proliferation rates of malignant cells, which allow enough time to have stromal interactions and induce fibrosis surrounding the invasive edge [ 44 ]. The fibrosis as well as the disorganized growth of malignant cells lead to an increase in acoustic impedance that causes posterior acoustic attenuation.…”

Section: Discussionmentioning

confidence: 99%

Survival outcome assessment for triple-negative breast cancer: a nomogram analysis based on integrated clinicopathological, sonographic, and mammographic characteristics

et al. 2022

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Objective This study aimed to incorporate clinicopathological, sonographic, and mammographic characteristics to construct and validate a nomogram model for predicting disease-free survival (DFS) in patients with triple-negative breast cancer (TNBC). Methods Patients diagnosed with TNBC at our institution between 2011 and 2015 were retrospectively evaluated. A nomogram model was generated based on clinicopathological, sonographic, and mammographic variables that were associated with 1-, 3-, and 5-year DFS determined by multivariate logistic regression analysis in the training set. The nomogram model was validated according to the concordance index (C-index) and calibration curves in the validation set. Results A total of 636 TNBC patients were enrolled and divided into training cohort (n = 446) and validation cohort (n = 190). Clinical factors including tumor size > 2 cm, axillary dissection, presence of LVI, and sonographic features such as angular/spiculated margins, posterior acoustic shadows, and presence of suspicious lymph nodes on preoperative US showed a tendency towards worse DFS. The multivariate analysis showed that no adjuvant chemotherapy (HR = 6.7, 95% CI: 2.6, 17.5, p < 0.0005), higher axillary tumor burden (HR = 2.7, 95% CI: 1.0, 7.1, p = 0.045), and ≥ 3 malignant features on ultrasound (HR = 2.4, CI: 1.1, 5.0, p = 0.021) were identified as independent prognostic factors associated with poorer DFS outcomes. In the nomogram, the C-index was 0.693 for the training cohort and 0.694 for the validation cohort. The calibration plots also exhibited excellent consistency between the nomogram-predicted and actual survival probabilities in both the training and validation cohorts. Conclusions Clinical variables and sonographic features were correlated with the prognosis of TNBCs. The nomogram model based on three variables including no adjuvant chemotherapy, higher axillary tumor load, and more malignant sonographic features showed good predictive performance for poor survival outcomes of TNBC. Key Points • The absence of adjuvant chemotherapy, heavy axillary tumor load, and malignant-like sonographic features can predict DFS in patients with TNBC. • Mammographic features of TNBC could not predict the survival outcomes of patients with TNBC. • The nomogram integrating clinicopathological and sonographic characteristics is a reliable predictive model for the prognostic outcome of TNBC.

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“…It forms a blurred mixed zone between the tumor and the tissues and complex edge. Besides, the complex interstitial components and hyaline transformation of malignant lesions often lead to scattering of acoustic signals [ 10 , 11 ]. During the decision process, the specialists often consider the orientation, posterior shadowing (PS), edge indistinctness (EI), and shape complexity (SC) of the tumors as essential features to identify them as benign or malignant.…”

Section: Methodsmentioning

confidence: 99%

“…But here we only use the first moment as it is sufficient to provide a score that could differentiate PS regions of different BUS images effectively. Accordingly, we substituted p � 0 and q � 2 in equation (11) and defined the PS score as…”

Section: Computation Of the Ps Score Of Posterior Shadowingmentioning

confidence: 99%

Multi‐Features‐Based Automated Breast Tumor Diagnosis Using Ultrasound Image and Support Vector Machine

Zhuang

Yang

Zhuang

et al. 2021

Computational Intelligence and Neuroscience

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Breast ultrasound examination is a routine, fast, and safe method for clinical diagnosis of breast tumors. In this paper, a classification method based on multi-features and support vector machines was proposed for breast tumor diagnosis. Multi-features are composed of characteristic features and deep learning features of breast tumor images. Initially, an improved level set algorithm was used to segment the lesion in breast ultrasound images, which provided an accurate calculation of characteristic features, such as orientation, edge indistinctness, characteristics of posterior shadowing region, and shape complexity. Simultaneously, we used transfer learning to construct a pretrained model as a feature extractor to extract the deep learning features of breast ultrasound images. Finally, the multi-features were fused and fed to support vector machine for the further classification of breast ultrasound images. The proposed model, when tested on unknown samples, provided a classification accuracy of 92.5% for cancerous and noncancerous tumors.

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Predicting Molecular Subtypes of Breast Cancer with Mammography and Ultrasound Findings: Introduction of Sono-Mammometry Score

Cited by 6 publications

References 23 publications

Association between ultrasound BI-RADS signs and molecular typing of invasive breast cancer

Association between ultrasound BI-RADS signs and molecular typing of invasive breast cancer

Survival outcome assessment for triple-negative breast cancer: a nomogram analysis based on integrated clinicopathological, sonographic, and mammographic characteristics

Multi‐Features‐Based Automated Breast Tumor Diagnosis Using Ultrasound Image and Support Vector Machine

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