Breast Sclerosing Adenosis and Accompanying Malignancies

Huang, Naisi; Chen, Jiajian; Xue, Jian; Yu, Baohua; Chen, Yanqiong; Yang, Wentao; Shao, Zhimin; Wu, Jiong

doi:10.1097/md.0000000000002298

Cited by 10 publications

(9 citation statements)

References 25 publications

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“…MRI features of SA described in the published literature are scarce. [9,12] These reports state that SA has a wide spectrum of appearances, such as enhancing mass, non-mass enhancement, structure distortion, even negative or not specified, which are mainly consistent with our findings. The majority of SA lesions showed low signal on T1-weighted images, high signal on T2-weighted images, and mass-like enhancement after the contrast agent administration in our series.…”

Section: Discussionsupporting

confidence: 92%

“…[6–7] And this infiltrating-like appearance on histopathology in SA sometimes leads to mimic invasive carcinoma regardless of clinical and radiological reports. [8–12] Especially, its mammographic patterns of calcifications in some SA may be difficult to differentiate from carcinoma. [13]…”

Section: Introductionmentioning

confidence: 99%

“…However, imaging findings of SA have been reported insufficiently, and there are only few articles which emphasize the mammographic and sonographic findings of SA, [7–8,12–15] and few articles describes the magnetic resonance imaging (MRI) features of SA of the breast. [9,12] The purpose of this study is to describe and assess the clinical features and image findings of SA on mammograms, sonograms, and MRI as well as to discover the best method for accurately determining this disease.…”

Section: Introductionmentioning

confidence: 99%

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Radiological and clinical findings in sclerosing adenosis of the breast

et al. 2019

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To study the imaging and clinical features of breast sclerosing adenosis (SA), and to enhance the recognition of this disease, as well as to help the clinic to give a correct diagnosis.Imaging findings were retrospectively reviewed in 47 women with SA lesions confirmed by pathology (including 39 cases of mammography, 40 cases of ultrasound [US], and 34 cases magnetic resonance imaging [MRI]).Of 47 patients confirmed with SA, 18 cases were pure SA, and 29 cases coexist with other proliferative lesions and malignancies; the maximum diameter of SA lesions was 0.5 to 3.5 cm with an average of 1.6 cm. On the mammogram of 39 SA cases, the percentage of architectural distortion, calcifications, mass/nodular, asymmetric density, and mass combining with calcifications were 30.8%, 23.1%, 17.9%, 12.8%, and 7.7%, respectively; and 3 cases had no abnormal findings. On the sonogram (excluding 5 normal finding cases), the majority of lesions showed regular shaped (57.1%), well defined margined (60.0%), heterogenous low echoed (71.4%) nodulus. 85.3% lesions showed high signal on T2-weighted images, and all lesions were enhanced markedly, including 82.4% lesions appearing mass-like enhancement (17 star-shaped enhanced masses included); and the percentage of the time-signal intensity curve in type 1, type 2, and type 3 were 52.9%, 41.2%, and 5.9%, respectively. If the category breast imaging-reporting and data system ≥4b was considered to be a suspicious malignant lesion, the misdiagnostic rates of mammography, US, and MRI would be 17.9%, 17.5%, and 35.3%, respectively.The SA lesions are small and can occur with other diseases histologically. The majority of SA lesions showed distortion or calcifications on mammograms, low echo-level nodules with heterogenous echo on US and mass-like lesion with or without star shape on enhanced MRI.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Radiological and clinical findings in sclerosing adenosis of the breast

et al. 2019

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“…SA can occur in all age groups, especially in 45–55 years old, some scholars believed that its pathogenesis may be related to the disorder of estrogen secretion and metabolism 5 . In this study, the median age of SA was 47.03 years, and the median age of SA associated with malignant lesions was 49.24 years, consistent with the median age of breast cancer in China, which inconsistent with some scholars' belief that the existence of SA will advance the age of breast cancer 6–8 . In a cohort of 13 434 women followed up for a median of 15.7 years, Visscher et al 9 found that the risk of breast cancer in patients with SA increased by two times.…”

Section: Discussioncontrasting

confidence: 80%

“…Yoshida et al 10 found that SA is an independent risk factor for synchronous bilateral breast cancer, and breast cancer occurring on the background of SA often has biologic characteristics of bilateral breast cancer. A study by Huang et al 7 showed 3.2% (240/722) of SA associated with malignant lesions, and 15% concurrent contralateral breast cancer. By contrast, 19.3% (17/88) of SA in this study associated with malignant lesions, 1 (6.25%) had contralateral breast cancer at the same time.…”

Section: Discussionmentioning

confidence: 98%

Value of multimodal imaging in the diagnosis of breast sclerosing adenosis associated with malignant lesions

Chen

Dai

et al. 2022

J of Clinical Ultrasound

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Aim To explore the diagnostic value of multimodal imaging techniques, including automatic breast volume scanner (ABVS), mammography (MG), and magnetic resonance (MRI) in breast sclerosing adenosis (SA) associated with malignant lesions. Methods From January 2018 to October 2020, 76 patients (88 lesions) with pathologically confirmed as SA associated with malignant or benign lesions were retrospective analyzed. All patients completed ABVS examination, 58 patients (67 lesions) with MG and 50 patients (62 lesions) with MRI were also completed before biopsy or surgical excision, of which, six patients (eight lesions) diagnosed as Breast Imaging Reporting and Data System (BI‐RADS) category 3 by all imaging examinations underwent surgical excision without biopsy, other 70 patients (80 lesions) with BI‐RADS category 4 or above by any imaging examination completed biopsy, including 65 patients (75 lesions) were further surgical excised and the other five patients (five lesions) were just followed up. All lesions were retrospectively described and classified, and were divided into benign group and malignant group according to their pathological results. Image features of different examination methods between the two groups were compared and analyzed. A ROC curve was established using the sensitivity of BI‐RADS categories to predict malignant lesions in different imaging techniques as the ordinate and 1‐specificity as the abscissa. Results 88 lesions including 26 purely SA and 45 SA associated with benign lesions were classified as benign group, and the remaining 17 SA associated with malignant lesions were classified as malignant group. On ABVS, 40 mass lesions, their heterogeneous echo, not circumscribed margin and coronal convergence signs were statistically significant for malignant lesions (p < .05), but the remain 48 nonmass lesions lack specific sonographic features. On MG, 12 showed negative results, 55 showed with microcalcification, mass, structural distortion, and asymmetric density shadow, of which 11 lesions had the above two signs at the same time, but only microcalcification had statistical difference between the two groups. 35 mass enhanced lesions and 27 nonmass enhanced lesions on MRI, but there were no significant difference between their pathological results. Time signal intensity curves showed no differences, but ADC value <1.10 × 10−3 mm2/s is more significant in malignant lesions (p < .05). The area under the ROC curve (AUC) of BI‐RADS classification of ABVS, MG, and MRI in the diagnosis of malignant lesions were 0.611, 0.474, and 0.751, respectively, and the AUC of the combined diagnosis of the three was 0.761. Conclusion Mass lesions with heterogeneous echo, not circumscribed margin and coronal convergence sign on ABVS, microcalcification on MG and the ADC value <1.10 × 10−3 mm2/s on MRI are significant signs for SA associated with malignant lesions. The combined diagnosis of the three methods was the highest, and the following were MRI, ABVS, and MG. Therefore, be cognizant of significant...

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A deep learning model for breast ductal carcinoma in situ classification in whole slide images

Kanavati¹,

Ichihara

2022

Virchows Arch

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The pathological differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) is of pivotal importance for determining optimum cancer treatment(s) and clinical outcomes. Since conventional diagnosis by pathologists using microscopes is limited in terms of human resources, it is necessary to develop new techniques that can rapidly and accurately diagnose large numbers of histopathological specimens. Computational pathology tools which can assist pathologists in detecting and classifying DCIS and IDC from whole slide images (WSIs) would be of great benefit for routine pathological diagnosis. In this paper, we trained deep learning models capable of classifying biopsy and surgical histopathological WSIs into DCIS, IDC, and benign. We evaluated the models on two independent test sets (n=1,382, n=548), achieving ROC areas under the curves (AUCs) up to 0.960 and 0.977 for DCIS and IDC, respectively.

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Breast Sclerosing Adenosis and Accompanying Malignancies

Cited by 10 publications

References 25 publications

Radiological and clinical findings in sclerosing adenosis of the breast

Radiological and clinical findings in sclerosing adenosis of the breast

Value of multimodal imaging in the diagnosis of breast sclerosing adenosis associated with malignant lesions

A deep learning model for breast ductal carcinoma in situ classification in whole slide images

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