Value of Ultrasonographic Features for Assessing Malignant Potential of Complex Cystic Breast Lesions

Yao, Jinpeng; Hao, Yu-Zhi; Chang, Qing; Geng, Chengyun; Chen, Yu; Zhao, Wenpeng; Song, Yan; Zhou, Xiang

doi:10.7863/ultra.16.05012

Cited by 15 publications

(7 citation statements)

References 14 publications

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“…Fatma Kulali et al 15 found that complex C-SNs of the breast are usually predominantly benign nodules with pathology of fibroadenomatoid/fibrocystic changes and malignant nodules with pathology of intraductal papillary carcinomas, and cystic lesions are usually more common with benign lesions. However, C-SNs have a wide probability of malignancy in previous studies (20–40%) 16 , 17 . Although there have been more studies in the last decade to determine the benignity and malignancy of complex cystic nodules of the breast, there is still no consensus on the specific ultrasound features.…”

Section: Discussionmentioning

confidence: 87%

Deep learning and ultrasound feature fusion model predicts the malignancy of complex cystic and solid breast nodules with color Doppler images

Hou

Tang

et al. 2023

Sci Rep

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This study aimed to evaluate the performance of traditional-deep learning combination model based on Doppler ultrasound for diagnosing malignant complex cystic and solid breast nodules. A conventional statistical prediction model based on the ultrasound features and basic clinical information was established. A deep learning prediction model was used to train the training group images and derive the deep learning prediction model. The two models were validated, and their accuracy rates were compared using the data and images of the test group, respectively. A logistic regression method was used to combine the two models to derive a combination diagnostic model and validate it in the test group. The diagnostic performance of each model was represented by the receiver operating characteristic curve and the area under the curve. In the test cohort, the diagnostic efficacy of the deep learning model was better than traditional statistical model, and the combined diagnostic model was better and outperformed the other two models (combination model vs traditional statistical model: AUC: 0.95 > 0.70, P = 0.001; combination model vs deep learning model: AUC: 0.95 > 0.87, P = 0.04). A combination model based on deep learning and ultrasound features has good diagnostic value.

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Section: Discussionmentioning

confidence: 87%

Deep learning and ultrasound feature fusion model predicts the malignancy of complex cystic and solid breast nodules with color Doppler images

Hou

Tang

et al. 2023

Sci Rep

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“…The malignancy rate of complex cysts was noted as 36% (18/50) 9 . Yao et al 17 have categorized 79 complex breast lesions into four groups according to sonographic findings. Similar to ours, they found malignancy rate was higher in type 3 and 4 lesions.…”

Section: Discussionmentioning

confidence: 99%

Outcomes in Sonographically Categorized Complex Cystic Breast Lesions

Kulalı

Guner

2021

J of Ultrasound Medicine

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Objectives To investigate outcomes of patients with complex cystic breast lesions and to determine malignancy rates for each sonographic category. Material and Methods A total of 124 women with a mean age of 45 were enrolled in this retrospective study. Complex cysts were classified into four categories according to sonographic findings (thick septa/wall, intramural nodule, solid/cystic ratio) by two radiologists. Size, margin, short‐to‐long axis ratio, and vascularity were also noted. The relationship between sonographic features and histopathological/follow‐up results was evaluated. Results Of 124 complex cysts, 11 were malignant and 113 were benign. There were 31 with thick septa/wall (category 1), 14 with intramural nodule (category 2), 60 with solid/cystic ratio < 1 (category 3), and 19 with solid/cystic ratio > 1 (category 4). Among 11 malignant tumors, six intraductal papillary carcinomas and three invasive ductal carcinomas were in category 3, whereas one invasive ductal carcinoma was in category 1 and one was in category 4. Most of malignant lesions (9/11, 82%) were in category 3. Most of benign lesions (96/113, 85%) were fibroadenomatoid/fibrocystic changes. The presence of vascularity (96%), irregular margin (94%), and short‐to‐long axis ratio ≥ 1 (94%) had higher accuracy rates for diagnosis of malignancy. Conclusion The malignancy rate was 8.8% in our study. Besides internal morphological features, other sonographic features should be considered in the evaluation of complex cystic breast lesions. Due to substantial risk of malignancy and the overlapping sonographic features of benign and malignant lesions, tissue sampling of all complex cysts should be performed.

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“…До дифузної форми можна зарахувати всі види так званих мастопатій, а до вузлової -доброякісні пухлини. Розподіл дисгормональних дисплазій на дифузну та вузлову має практичне значення: хворих із дифузними формами лікують консервативно, а з вузловими -оперативно [33,34].…”

Section: гінекологіяunclassified

“…Це виявляється при пальпації, під час ультразвукового дослідження, на рентгенограмі грудної залози (мамографія). Вирішальне значення для вибору методу лікування має диференційна діагностика, під час якої визначають доброякісне чи злоякісне походження пухлинного вузла [33,35].…”

Section: гінекологіяunclassified

“…У щоденній гінекологічній практиці поєднана патологія матки і грудних залоз спостерігається доволі часто. Багатьма сучасними дослідженнями виявлений прямий сильний кореляційний зв'язок патології грудних залоз із такими гінекологічними захворюваннями, як міома матки (85%), аденоміоз (67%), гіперплазія ендометрія (82%) [33,39,41]. Результати деяких досліджень свідчать про значне збільшення частоти цієї патології саме в жінок перименопаузального періоду [42].…”

Section: гінекологіяunclassified

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Modern state of problem of the combined pathology of uterus and mammary glands at women of perimenopause age

Kruk

2021

P&R

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Among the most common pathological processes in gynecological practice in women of the perimenopausal period are the combined pathology of the uterus and mammary glands. Despite the long history of the study, this problem continues to be the focus of attention of domestic and foreign researchers because of the high risk of malignant degeneration. Particular attention deserves attention to timely quality diagnostics and the development of tactics for the management of patients with combined pathology in perimenopause, since it is during this period of life that women clinicians have the greatest difficulty in choosing the real therapeutic effect.

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Value of Ultrasonographic Features for Assessing Malignant Potential of Complex Cystic Breast Lesions

Abstract: US is an important adjunct to evaluate the malignant potential of complex cystic lesions.

Cited by 15 publications

References 14 publications

Deep learning and ultrasound feature fusion model predicts the malignancy of complex cystic and solid breast nodules with color Doppler images

Deep learning and ultrasound feature fusion model predicts the malignancy of complex cystic and solid breast nodules with color Doppler images

Outcomes in Sonographically Categorized Complex Cystic Breast Lesions

Modern state of problem of the combined pathology of uterus and mammary glands at women of perimenopause age

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