Mucinous versus medullary breast carcinoma: mammography, ultrasound, and MRI findings

Pintican, Roxana; Duma, Mihaela; Chiorean, Angelica; Fetică, Bogdan; Badan, M; Bura, Vlad; Szep, Madalina; Feier, Diana; Dudea, Sorin M

doi:10.1016/j.crad.2019.12.024

Cited by 14 publications

(9 citation statements)

References 32 publications

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“…The patient, older than the reported median age of 64, did not have a documented history of any conditions causing an estrogen-testosterone disruption. In terms of imaging, this patient presented with an isoechoic mass on ultrasound, consistent with imaging features of a mucinous tumor [21] . Although he did have a history of thyroid cancer, a pathogenic variant-related malignancy, genetic testing was negative and it is quite possible that a genetic mechanism by which this patient developed breast cancer has not yet been uncovered.…”

Section: Discussionsupporting

confidence: 53%

Mucinous carcinoma in a male patient: Diagnosis and management of breast cancer in male patients

Ahmed

Wagner

Jordan

2022

Radiology Case Reports

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Section: Discussionsupporting

confidence: 53%

Mucinous carcinoma in a male patient: Diagnosis and management of breast cancer in male patients

Ahmed

Wagner

Jordan

2022

Radiology Case Reports

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“…Second, the distribution of pathological subtypes of breast cancer included in this study was unbalanced, especially for the specific pathological types such as mucinous or medullary breast cancer. In addition, the sample size was relatively small and the specific pathological types had different histological substrates that manifest as different imaging features on US ( 51 , 52 ), which may have resulted in bias. Third, large dimension lesions were not included in this study, which could have caused spectrum bias in patient selection.…”

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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“…The first explanation may be found in the presence of abundant necrosis, with a predominant cystic component, seen in these highly aggressive tumors. In addition, in our study, 10% of the tumors were of special sub-types, such as mucinous-, medullary-, or adenoid cystic-type tumors, which may have a minor solid component that could further contribute to this appearance [ 19 , 20 ]. Therefore, we suggest that the BGR aspect seen in solid tumors be re-named as “false BGR” appearance.…”

Section: Discussionmentioning

confidence: 99%

Are Mutation Carrier Patients Different from Non-Carrier Patients? Genetic, Pathology, and US Features of Patients with Breast Cancer

Pintican

Chiorean²,

Duma³

et al. 2022

Cancers

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The purpose of this study is to evaluate the relationship between the pathogenic/likely pathogenic mutations, US features, and histopathologic findings of breast cancer in mutation carriers compared to non-carrier patients. Methods: In this retrospective study, we identified 264 patients with breast cancer and multigene panel testing admitted to our clinic from January 2018 to December 2020. Patient data US findings, US assessment of the axilla, multigene panel tests, histopathology, and immunochemistry reports were reviewed according to the BI-RADS lexicon. Results: The study population was comprised of 40% pathogenic mutation carriers (BRCA1, BRCA2, CHEK2, ATM, PALB, TP 53, NBN, MSH, BRIP 1 genes) and 60% mutation-negative patients. The mean patient age was 43.5 years in the carrier group and 44 years in the negative group. Carrier patients developed breast cancer with benign morphology (acoustic enhancement, soft elastography appearance) compared to non-carriers (p < 0.05). A tendency towards specific US features was observed for each mutation. BRCA1 carriers were associated with BC with microlobulated margins, hyperechoic rim, and soft elastography appearance (p < 0.05). Estrogen receptor (ER)-negative tumors were associated with BRCA1, TP53, and RAD mutations, while BRCA2 and CHEK2 were associated with ER-positive tumors. Conclusions: Patients with pathogenic mutations may exhibit BC with benign US features compared to negative, non-carrier patients. BRCA1, TP53, and RAD carriers account for up to one third of the ER tumors from the carrier group. Axillary US performed worse in depicting involved lymph nodes in carrier patients, compared to negative patients.

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Mucinous versus medullary breast carcinoma: mammography, ultrasound, and MRI findings

Cited by 14 publications

References 32 publications

Mucinous carcinoma in a male patient: Diagnosis and management of breast cancer in male patients

Mucinous carcinoma in a male patient: Diagnosis and management of breast cancer in male patients

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

Are Mutation Carrier Patients Different from Non-Carrier Patients? Genetic, Pathology, and US Features of Patients with Breast Cancer

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