Contrast-enhanced ultrasound to predict malignant upgrading of atypical ductal hyperplasia.

BACKGROUND: A malignancy might be found at surgery in cases of atypical ductal hyperplasia (ADH) diagnosed via US-guided core needle biopsy (CNB). The objective of this study was to investigate the diagnostic performance of contrast-enhanced ultrasound (CEUS) in predicting ADH diagnosed by US-guided CNB that was upgraded to malignancy after surgery. METHODS: In this retrospective study, 110 CNB-diagnosed ADH lesions in 109 consecutive women who underwent US, CEUS, and surgery between June 2018 and June 2023 were included. CEUS was incorporated into US BI-RADS and yielded a CEUS-adjusted BI-RADS. The diagnostic performance of US BI-RADS and CEUS-adjusted BI-RADS for ADH were analyzed and compared. RESULTS: The mean age of the 109 women was 49.7 years ± 11.6 (SD). The upgrade rate of ADH at CNB was 48.2% (53 of 110). The sensitivity, specificity, positive predictive value, and negative predictive value of CEUS for identification of malignant upgrading were 96.2%, 66.7%,72.9%, and 95.0%, respectively, based on BI-RADS category 4B threshold. The two false-negative cases were low-grade ductal carcinoma in situ. Compared with the US, CEUS-adjusted BI-RADS had better specificity for lesions smaller than 2 cm (76.7% vs. 96.7%, P = 0.031). After CEUS, 16 (10 malignant and 6 nonmalignant) of the 45 original US BI-RADS category 4A lesions were up-classified to BI-RADS 4B, and 3 (1 malignant and 2 nonmalignant) of the 41 original US BI-RADS category 4B lesions were down-classified to BI-RADS 4A. CONCLUSIONS: CEUS is helpful in predicting malignant upgrading of ADH, especially for lesions smaller than 2 cm and those classified as BI-RADS 4A and 4B on ultrasound.

Combination of Breast Ultrasound With Magnetic Resonance Imaging in the Diagnosis of Non-mass-like Breast Lesions Detected on Ultrasound: A New Integrated Strategy to Improve Diagnostic Performance.

OBJECTIVE: The aim of the work described here was to evaluate the diagnostic performance of a new integrated strategy using breast ultrasound (US) combined with magnetic resonance imaging (MRI) to differentiate benign and malignant breast non-mass-like lesions (NMLs) detected on US. METHODS: From October 2017 to January 2021, 183 NMLs detected on US that had undergone MRI examinations were included in this respective study. Pathological results were used as the reference standard. The integrated diagnostic strategy of breast US combined with MRI based on a combination of MRI Breast Imaging Reporting and Data System (BI-RADS) with discriminant sonographic indicators highly associated with malignancy was established and validated in a cohort of 61 women. The diagnostic performances of US, MRI and the combined method were calculated and compared. RESULTS: In the training set, the area under the receiver operating characteristic curve (AUC), sensitivity and specificity of US, MRI and the integrated diagnostic strategy using US combined with MRI for NMLs were 0.730, 93.7% and 52.3%; 0.849, 94.7% and 75.0%; and 0.901, 92.6% and 87.5%, respectively. Compared with US or MRI alone, the integrated diagnostic strategy significantly increased the AUC (p < 0.001, p = 0.007) and specificity (p < 0.001, p = 0.034) while maintaining high sensitivity (p = 0.774, p = 0.551). In the validation set, the integrated strategy of US combined with MRI (AUC = 0.899) also had good performance compared with US (AUC = 0.728) or MRI (AUC = 0.838). CONCLUSION: The integrated diagnostic strategy of US combined with MRI exhibited good performance for breast NMLs compared with either modality used alone, which can improve the diagnostic specificity while maintaining high sensitivity.

Benign Phyllodes Tumors: Comparison of Prognosis among Three Different Surgical Approaches.

Purpose: To evaluate the prognosis of patients with benign phyllodes tumors (PTs) treated by different surgical methods and to explore the influencing factors of local recurrence. Methods: We retrospectively analyzed 215 benign PTs from 193 patients who underwent surgery at Chinese PLA General Hospital between October 2008 and December 2020. We stratified our analysis according to surgical factors and explored the clinicopathological factors to influence local recurrence. Results: Among 193 patients, a total of 17 (8.8%, 17/193) recurred during follow-up. There were 89 patients in the US-VAE group, of whom 6 (6.7%) recurred; 8 of 57 patients (14%) in the local lumpectomy group recurred, while 3 of 47 patients (6.4%) in the extended lumpectomy group recurred (P=0.252). Multivariate logistic regression analysis showed that tumor diameter, mitosis, and history of breast myoma were independent risk factors for tumor recurrence (P=0.005, P=0.006, and P=0.004, respectively). The intraoperative blood loss, operation time, and scar length of the US-VAE group were shorter than those of the other two groups (P < 0.05). Conclusion: Negative surgical margins of benign PTs can obtain similar prognosis as negative surgical margins >10 mm. Therefore, we recommend that a follow-up observation policy be adopted for patients with unexpected benign PTs, rather than unnecessary open surgical resection. Patients' maximum tumor diameter, mitosis, and fibroadenoma history were independent predictors for recurrence of benign PTs.

Conventional ultrasound combined with contrast-enhanced ultrasound: could it be helpful for the diagnosis of thoracic wall recurrence after mastectomy?

OBJECTIVES: To develop a predictive model using conventional ultrasound combined with CEUS to identify thoracic wall recurrence after mastectomy. METHODS: A total of 162 women with pathologically confirmed thoracic wall lesions (benign 79, malignant 83; median size 1.9 cm, ranging 0.3-8.0 cm) underwent a mastectomy and were checked by both conventional ultrasound and CEUS and were retrospectively included. Logistic regression models of B-mode ultrasound (US) and color Doppler flow imaging (CDFI) with or without CEUS were established to assess the thoracic wall recurrence after mastectomy. The established models were validated by bootstrap resampling. The models were evaluated using calibration curve. The clinical benefit of models were assessed using decision curve analysis. RESULTS: The area under the receiver characteristic was 0.823 (95% CI: 0.76, 0.88) for model using US alone, 0.898 (95% CI: 0.84, 0.94) for model using US combined with CDFI, and 0.959 (95% CI: 0.92, 0.98) for model using US combined with both CDFI and CEUS. The diagnostic performance of the US combined with CDFI was significantly higher than that of the US alone (0.823 vs 0.898, p = 0.002) but significantly lower than that of the US combined with both CDFI and CEUS (0.959 vs 0.898, p < 0.001). Moreover, the unnecessary biopsy rate of the US combined with both CDFI and CEUS was significantly lower than that of the US combined with CDFI (p = 0.037). CONCLUSIONS: Compared to B-mode ultrasound and CDFI, CEUS improves the diagnostic performance to evaluate thoracic wall recurrence after mastectomy. KEY POINTS: • CUES is an effective supplementary method for US in the diagnosis of thoracic wall recurrence after mastectomy. • CEUS combined with both US and CDFI can significantly improve the accuracy of diagnosis of thoracic wall recurrence after mastectomy. • CEUS combined with both US and CDFI can reduce the rate of unnecessary biopsy of thoracic wall lesions after mastectomy.

Collagen fiber features and COL1A1: are they associated with elastic parameters in breast lesions, and can COL1A1 predict axillary lymph node metastasis?

BACKGROUND: This study aimed to explore whether collagen fiber features and collagen type I alpha 1 (COL1A1) are related to the stiffness of breast lesions and whether COL1A1 can predict axillary lymph node metastasis (LNM). METHODS: Ninety-four patients with breast lesions were consecutively enrolled in the study. Amongst the 94 lesions, 30 were benign, and 64 were malignant (25 were accompanied by axillary lymph node metastasis). Ultrasound (US) and shear wave elastography (SWE) were performed for each breast lesion before surgery. Sirius red and immunohistochemical staining were used to examine the shape and arrangement of collagen fibers and COL1A1 expression in the included tissue samples. We analyzed the correlation between the staining results and SWE parameters and investigated the effectiveness of COL1A1 expression levels in predicting axillary LNM. RESULTS: The optimal cut-off values for Emax, Emean, and Eratio for diagnosing the benign and malignant groups, were 58.70 kPa, 52.50 kPa, and 3.05, respectively. The optimal cutoff for predicting axillary LNM were 107.5 kPa, 85.15 kPa, and 3.90, respectively. Herein, the collagen fiber shape and arrangement features in breast lesions were classified into three categories. One-way analysis of variance (ANOVA) showed that Emax, Emean, and Eratio differed between categories 0, 1, and 2 (P < 0.05). Meanwhile, elasticity parameters were positively correlated with collagen categories and COL1A1 expression. The COL1A1 expression level > 0.145 was considered the cut-off value, and its efficacy in benign and malignant breast lesions was 0.808, with a sensitivity of 66% and a specificity of 90%. Furthermore, when the COL1A1 expression level > 0.150 was considered the cut-off, its efficacy in predicting axillary LNM was 0.796, with sensitivity and specificity of 96% and 59%, respectively. CONCLUSIONS: The collagen fiber features and expression levels of COL1A1 positively correlated with the elastic parameters of breast lesions. The expression of COL1A1 may help diagnose benign and malignant breast lesions and predict axillary LNM.

Ultrasonographic features of ductal carcinoma in situ: analysis of 219 lesions.

BACKGROUND: The purpose of this paper is to clarify the ultrasonographic features and classification of ductal carcinoma in situ (DCIS), and to evaluate the ability of ultrasonography in the prediction of DCIS. METHODS: The clinical data, gray-scale ultrasound images and pathological results of 219 DCIS lesions that detected in 203 consecutive patients who underwent ultrasonography and surgery in our hospital from January 1, 2014 to December 31, 2019 were collected retrospectively. Ultrasonographic features and classification of DCIS were summarized, and the accuracy of ultrasonography in predicting different ultrasonographic findings of DCIS were compared. RESULTS: Among the 219 DCIS lesions, 91 (41.6%) presented as mass-like lesions and 128 (58.4%) were non-mass-like lesions. For the 91 mass-like DCIS lesions, 79 were hypoechoic solid masses, 12 were cystic-solid structures. For the 128 non-mass-like DCIS lesions, 114 were hypoechoic areas, 10 were ductal dilatation accompanied with intraductal solid components, and 4 were multiple punctate echogenic foci only. The diagnostic accuracy of ultrasound for the 219 DCIS lesions was 81.7% (179/219). The diagnostic accuracy of mass-like DCIS lesions was 90.1% (82/91), which was significantly higher than that in non-mass-like DCIS lesions [75.8% (97/128), P=0.007]. The diagnostic accuracy of hypoechoic solid masses was significantly higher than those of the other ultrasonographic findings (P=0.002). Ducts abnormalities were detected in 45 (20.5%) lesions and punctate echogenic foci in 134 (61.2%) lesions. The diagnostic accuracy of lesions with ducts abnormalities was 93.3% (42/45), which was significantly higher than that in lesions without ducts abnormalities [78.7% (137/174), P=0.024]. The diagnostic accuracy of lesions with punctate echogenic foci was 92.5% (124/134), which was significantly higher than that in lesions without punctate echogenic foci [64.7% (55/85), P=0.000]. CONCLUSIONS: DCIS lesions can effectively be recognized as mass-like lesions and non-mass-like lesions by ultrasound. Hypoechoic areas and hypoechoic solid masses were the most common ultrasonographic features of DCIS. Ducts abnormalities and punctate echogenic foci were helpful for the diagnosis of DCIS.