Association between ultrasound morphologic features and histopathological findings of lobular carcinoma

Malherbe, Kathryn; Bresser, Philippa

doi:10.1002/jmrs.336

Cited by 7 publications

(3 citation statements)

References 25 publications

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“…Lobular tumors are also more likely to exhibit irregular contours and more diffuse margins and have a higher likelihood of satellite foci (29). We did not find a higher rate of underestimation in lobular tumors, although they made up only 10 patients of our cohort.…”

Section: Discussionmentioning

confidence: 50%

Radiological Underestimation of Tumor Size Influences the Success Rate of Re-Excision after Breast-conserving Surgery

Simpson¹,

Allan²,

McFall³

2021

EJBH

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Objective: Failure to achieve adequate margins after breast-conserving surgery often leads to re-excision, either by repeat breast-conserving surgery (BCS) or by mastectomy. Despite the high frequency of this problem, the success rate of achieving adequate margins by repeat BCS is not well documented. The objective of this study was to determine the success rate of repeat BCS and identify the factors influencing that rate. Materials and Methods:A retrospective review was performed of all women undergoing repeat BCS for inadequate margins after initial BCS in our breast unit between 2013 and 2019. Univariate and multivariate analyses were carried out to identify the factors influencing how often adequate margins were achieved after repeat BCS.Results: One hundred fifty-four patients underwent repeat BCS after initially inadequate margins, of which adequate margins were achieved in 82%. Patients with successful repeat BCS had smaller tumors, had less underestimation of tumor size on imaging, and were less likely to have had cavity shaves taken at their initial BCS. A tumor size more than 50% larger than predicted by imaging was independently associated with failure of repeat BCS in multivariate analysis (odds ratio: 3.6, 95% CI: 1.41-9.20, p = 0.007). Underestimation of tumor size by imaging was commoner and more extensive in patients with larger tumors and those with ductal carcinoma in situ. Conclusion:Re-excision by cavity shaves has a high success rate and should be offered to all patients who are deemed suitable for the procedure. Patients whose tumors are more than 50% larger than predicted by imaging should be counseled about the higher risk of failure.

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Section: Discussionmentioning

confidence: 50%

Radiological Underestimation of Tumor Size Influences the Success Rate of Re-Excision after Breast-conserving Surgery

Simpson¹,

Allan²,

McFall³

2021

EJBH

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“…In contrast, the morphometric features characterize the shape and contour of a lesion and are essentially independent of the system settings and machines ( 22 , 44 ). More importantly, the morphologic traits of breast cancer are associated with histological findings ( 21 , 45 , 46 ), which can provide valuable information for deriving robust multidisciplinary models ( 47 ). In this study, we found that most of the morphometric features differed significantly between benign and malignant groups, and the contributions of the selected features to the prediction model were as follows: Solidity > Circularity > Minor Axis.…”

Section: Discussionmentioning

confidence: 99%

Development and External Validation of a Simple-To-Use Dynamic Nomogram for Predicting Breast Malignancy Based on Ultrasound Morphometric Features: A Retrospective Multicenter Study

Zhang

Liu

et al. 2022

Front. Oncol.

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BackgroundWith advances in high-throughput computational mining techniques, various quantitative predictive models that are based on ultrasound have been developed. However, the lack of reproducibility and interpretability have hampered clinical use. In this study, we aimed at developing and validating an interpretable and simple-to-use US nomogram that is based on quantitative morphometric features for the prediction of breast malignancy.MethodsSuccessive 917 patients with histologically confirmed breast lesions were included in this retrospective multicentric study and assigned to one training cohort and two external validation cohorts. Morphometric features were extracted from grayscale US images. After feature selection and validation of regression assumptions, a dynamic nomogram with a web-based calculator was developed. The performance of the nomogram was assessed with respect to calibration, discrimination, and clinical usefulness.ResultsThrough feature selection, three morphometric features were identified as being the most optimal for predicting malignancy, and all regression assumptions of the prediction model were met. Combining all these predictors, the nomogram demonstrated a good discriminative performance in the training cohort and in the two external validation cohorts with AUCs of 0.885, 0.907, and 0.927, respectively. In addition, calibration and decision curves analyses showed good calibration and clinical usefulness.ConclusionsBy incorporating US morphometric features, we constructed an interpretable and easy-to-use dynamic nomogram for quantifying the probability of breast malignancy. The developed nomogram has good generalization abilities, which may fit into clinical practice and serve as a potential tool to guide personalized treatment. Our findings show that quantitative morphometric features from different ultrasound machines and systems can be used as imaging surrogate biomarkers for the development of robust and reproducible quantitative ultrasound dynamic models in breast cancer research.

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“…However, the characteristic of shape was rare to be used as a predictive factor in BC patients because it is difficult to evaluate in surgical specimens. US is suitable to evaluate the morphometric properties of a tumor by cine clips through the masses with a longitudinal axis and a transverse axis [ 22 ]. We concluded that the US characteristic of irregular shape was a higher risk factor for the patients with short-DFS compared with a round or oval shape with an OR value of 2.052.…”

Section: Discussionmentioning

confidence: 99%

Predictive Value of Ultrasound Characteristics for Disease-Free Survival in Breast Cancer

et al. 2022

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The main objective of this study was to determine the predictive value of US characteristics for disease-free survival (DFS) in BC patients. We retrospectively analyzed the ultrasonic images and clinical data of BC patients who had previously undergone breast surgery at least 10 years before study enrollment and divided them into a case group and a control group according to the cutoff value of 120 months for DFS. Correlation analysis was performed to identify US characteristics as independent predictors for DFS by multivariable logistic regression and Kaplan–Meier survival analysis. A total of 374 patients were collected, including 174 patients in the case group with short-DFS and 200 patients in the control group with long-DFS. Three US characteristics (size on US, mass shape, mass growth orientation) and two clinical factors (axillary lymph node (ALN), molecular subtypes) were identified as independent predictors for DFS (p < 0.05). The ROC curve showed good performance of the multivariate linear regression model with the area under the curve being 0.777. The US characteristics of large size, irregular shape, and nonparallel orientation were significantly associated with short-DFS, which is a promising supplementary for clinicians to optimize clinical decisions and improve prognosis in BC patients.

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Association between ultrasound morphologic features and histopathological findings of lobular carcinoma

Cited by 7 publications

References 25 publications

Radiological Underestimation of Tumor Size Influences the Success Rate of Re-Excision after Breast-conserving Surgery

Radiological Underestimation of Tumor Size Influences the Success Rate of Re-Excision after Breast-conserving Surgery

Development and External Validation of a Simple-To-Use Dynamic Nomogram for Predicting Breast Malignancy Based on Ultrasound Morphometric Features: A Retrospective Multicenter Study

Predictive Value of Ultrasound Characteristics for Disease-Free Survival in Breast Cancer

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