To analyze the clinical and ultrasonographic features of breast hamartoma.

A retrospective analysis was conducted on 61 lesions of 60 female patients with pathologically confirmed breast hamartoma who underwent surgical treatment at Peking Union Medical College Hospital from July 2002 to June 2023. The clinical data and ultrasonographic examination results were reviewed, and the characteristics of breast hamartoma were summarized.

All patients were female with an average age of (44.1±11.9) years. Breast hamartomas were predominantly located in the outer quadrants of the breast, with a medium diameter of 3.20 cm. The ultrasonographic features varied among cases. Typical sonographic characteristics of breast hamartoma included regular shape, clear borders, predominantly hypoechoic interior with intermingled linear or band-like hyperechoic areas, and poor vascularity on color Doppler imaging.

Breast hamartoma has certain clinical and sonographic characteristics. Ultrasonography is the preferred diagnostic method for breast hamartoma, providing important information for clinical diagnosis and treatment.

To explore the application value of a deep learning-based model for generating strain elastography images using breast grayscale ultrasound images.

A total of 1336 sets of ultrasound images of patients who underwent breast ultrasound examination at Xijing Hospital from May 2019 to June 2022 were retrospectively collected. A deep learning-based model for generating strain elastography images was constructed on the basis of generative adversarial network (GAN) in neural network. Then, 882 sets of images from the training set and 354 sets of images from the validation set were used to train and adjust the model, and 100 sets of images from the test set were additionally used to generate strain elastography images. The similarity was compared between the real elastography images and the generated elastography images. Four physicians of different seniority (2 senior and 2 junior) were selected to compare the differences between the two kinds of elastography images. Normalized cross-correlation (NCC) values were used to evaluate the similarity of the two kinds of elastography images and the authenticity score of reading physicians was obtained. Based on the Tsukuba's 5-point elastography scoring scale, Kappa test was applied to test the consistency of elastography scores of the four physicians. Receiver operating characteristic (ROC) curves were plotted to evaluate the performance of breast imaging reporting and data system (BI-RADS) classification in the diagnosis of benign and malignant breast lesions by different physicians based on the two kinds of elastography images.

The average NCC value for the similarity of the two kinds of elastography images in the test set was (0.70±0.08), with a median of 0.70 (range: 0.50 to 0.86). The average authenticity score of all the physicians was 0.49, with an average score of 0.45 for junior doctors and 0.53 for senior doctors, all of which were close to 0.50. The Kappa value of elastography scores of the four physicians was higher in the generated elastography image group than in the real elastography image group (Kappa values: 0.61 vs 0.57). There was no statistically significant difference in the area under ROC curve for each physician applying BI-RADS classification based on the two kinds of elastography images (P>0.05). Except for the specificity (P=0.0196) and positive predictive value (P=0.021) of one senior physician, there were no statistically significant differences in sensitivity, specificity, positive predictive value, or negative predictive value among other physicians (P>0.05).

The constructed deep learning-based model for generating strain elastography images using breast grayscale ultrasound images can generate elastography images similar to real elastography images, and the generated elastography images is comparable to real elastography in terms of diagnostic assistance.

To construct a clinical model, an imaging model, and a combined model for predicting pathological complete response (pCR) based on the clinicopathological characteristics and ultrasound imaging characteristics of breast cancer patients before neoadjuvant chemotherapy (NAC), and to compare the clinical value of the three models in predicting the efficacy of NAC.

A total of 202 female patients who underwent NAC for breast cancer at Huangshi Central Hospital from January 2019 to January 2024 and had the results of pathologic evaluation were retrospectively collected. The cases from two different hospital districts were classified into a training set (107 cases) and a validation set (95 cases). In the training set, univariate and multivariate logistic regression analyses were performed to identify clinically significant features and construct a clinical model. The minimum absolute contraction and selection operator regression were used to screen the radiomics features and establish a radiomics model. The Radscore of each patient was calculated according to the characteristic parameters and their regression coefficients. Multivariate logistic regression was then used to construct a combined prediction model based on statistically significant clinicopathological features and Radscore. Receiver operating characteristic (ROC) curve and decision curve were used to evaluate and verify the predictive efficacy and clinical value of the three models.

In the training set, hormone receptor (HR) status and human epidermal growth factor receptor 2 (HER2) status were included in the multivariate logistic regression to establish a clinical model. Lasso regression was used to select five best radiomics features, namely, contrast, correlation, entropy, gray unevenness, and percentage of run, to establish a radiomics model. Univariate logistic regression showed that Radscore was significantly different between patients with and without pCR. HR status (odds ratio [OR]: 0.31, 95% confidence interval [CI]: 0.15-0.64, P < 0.01), HER2 status (OR: 2.96, 95%CI: 1.43-6.12, P < 0.01), and Radscore (OR: 1.19, 95%CI: 1.07-1.33, P < 0.01) were included to build a combined model. In the training set, the area under the ROC curve (AUC) of the clinical model, radiomics model, and combined model in predicting pCR was 0.68, 0.75, and 0.82, respectively. In the validation set, the AUC of the clinical model, radiomics model, and combined model in predicting pCR was 0.68, 0.72, and 0.79, respectively. The combined model had the highest net benefit value in the decision curve analysis, followed by the radiomics model and the clinical model.

The clinical model, radiomics model, and combined model are all clinically valuable for predicting NAC efficacy in breast cancer, with the combined model having the best efficacy, predictive performance, and clinical applicability.

To evaluate the clinical value of automated breast ultrasound (ABUS) combined with immunohistochemistry in early prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients.

A total of 420 female breast cancer patients admitted to the Department of Breast Surgery, the First Affiliated Hospital of Air Force Military Medical University (Xijing Hospital) from March 2019 to June 2022 were included. All patients were confirmed to have invasive breast cancer by puncture pathology. All patients underwent ABUS examination before NAC. According to the postoperative pathological results, the patients were divided into either a pCR group (n=153) or a non-pathological complete response (npCR) group (n=267). Multivariate Logistic regression was used to identify the independent predictors of pCR in breast cancer. Three prediction models were constructed: ABUS feature prediction model, immunohistochemical prediction model, and ABUS combined with immunohistochemical prediction model. The receiver operating characteristic (ROC) curves of the three models were plotted to evaluate their performance. The area under the ROC curve (AUC) of the models was compared by the Delong test, and the optimal model was selected to construct a nomogram. The fitness of the model was analyzed by the Hosmer-Lemeshow test, and the Bootstrap method was used to verify the model internally. The calibration curve was drawn to evaluate the performance of the model, and the decision curve was used to evaluate the clinical benefit of the prediction model.

There were significant differences in estrogen receptor (ER) status, progesterone receptor (PR) status, human epidermal growth factor receptor (HER-2) status, Ki67 status, and molecular typing between the pCR group and npCR group before NAC (P<0.05 for all). There were also significant differences in skin invasion, morphology, posterior echo, retraction phenomenon on coronal images, and white wall sign on coronal images between the two groups before NAC (P<0.05 for all). Multivariate Logistic regression analysis showed that HER-2 status (odds ratio [OR]=4.396, 95% confidence interval [CI]: 2.089-9.25), molecular typing (HER-2 overexpression type: OR=4.124, 95%CI: 2.069-8.219; triple negative type (OR=4.775, 95%CI: 2.188-10.422), skin invasion (OR=0.110, 95%CI: 0.038-0.318), retraction phenomenon on coronal images (OR=0.416, 95%CI: 0.220-0.787), and white wall sign on coronal images (OR=11.192, 95%CI: 5.316-23.561) were independent predictors of pCR (P<0.05 for all). The Delong test showed that the AUC (0.855) of the combined model (nomogram) based on the ABUS model and immunohistochemical features was significantly higher than that of the immunohistochemical model (AUC=0.758; Z=5.11, P<0.001) and the ABUS model (AUC=0.774; Z=5.49, P<0.001); the AUC (0.774) of the ABUS model was slightly higher than that of the immunohistochemical model (AUC=0.758 ), but the difference was not statistically significant (Z=0.55, P=0.58). The Hosmer-Lemeshow test showed that the model fit well (χ2=6.175, P=0.519 ). The results of internal validation showed that the average C-index was 0.856 (95%CI: 0.810-0.886), indicating that the model had good stability. Calibration curve analysis showed that the prediction probability of the combined model was in good agreement with the actual probability. Decision curve analysis showed that the combined model had better clinical benefits in a wide range of thresholds.

The combined model based on ABUS features of pre-NAC tumors combined with immunohistochemistry can accurately predict pCR to NAC in breast cancer, which can provide a basis for the formulation of clinical treatment plans for breast cancer patients.

To investigate whether three-dimensional inversion imaging can improve the diagnosis of the nature of Breast Imaging Reporting and Data System (BI-RADS) category 4 breast masses to reduce unnecessary biopsies.

A total of 247 breast masses were collected from 243 patients who were diagnosed as having BI-RADS category 4 lesions by conventional ultrasound and underwent three-dimensional inversion imaging from September 2021 to June 2023 at the Second Affiliated Hospital of Anhui Medical University. Based on the distribution characteristics of dark grey and black areas within the mass in the inverted images, the diagnostic efficacy of conventional ultrasound alone and combined with three-dimensional inversion imaging for BI-RADS category 4 breast masses was compared by using a semi-quantitative 5-point inversion scoring method and plotting receiver operating characteristic (ROC) curves with pathological findings as the gold standard.

The area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of conventional ultrasound for identifying the nature of BI-RADS category 4 breast masses were 0.841, 83.8%, 93.3%, 74.8%, 77.8%, and 92.2%, respectively; the corresponding values of the combined diagnosis were 0.887, 88.7%, 90.0%, 87.4%, 87.1%, and 90.2%. The combined diagnosis resulted in 87 BI-RADS category 4a benign masses being downgraded to category 3, and did not result in malignant masses mistakenly downgraded to category 3, which would have prevented unnecessary biopsies of 84.5% (87/103) of category 4a masses.

Conventional ultrasound combined with three-dimensional inversion imaging has good diagnostic efficacy for benign and malignant breast masses, significantly improving the diagnosic specificity and positive predictive value and thus effectively reducing unnecessary biopsies of category 4a masses.

To construct a nomogram based on ultrasonic features and clinicopathological indicators and to explore its predictive value for axillary lymph node metastasis in patients with T1-2 breast cancer.

A total of 354 patients with histopathologically confirmed T1-2 breast cancer admitted to Xijing Hospital from January 2021 to September 2022 were included. According to whether there was axillary lymph node metastasis, the patients were divided into a metastatic group of 125 cases and a non-metastatic group of 229 cases. Univariate and multivariate Logistic regression analyses were used to screen independent predictors, and the axillary ultrasound model and comprehensive model (axillary ultrasound features + breast ultrasound features + clinicopathological indicators) were constructed. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive efficiency of the models, and the predictive efficiency was compared by the Delong's test. A nomogram of the comprehensive model was plotted, and the goodness of fit, calibration, and clinical utility of the model were evaluated by the Hosmer-Lemeshow test as well as calibration curve and decision curve analyses.

The ratio of long diameter to short diameter of lymph nodes, morphological typing of lymph nodes, maximum tumor diameter, architectural distortion, body mass index, histological grade, and estrogen receptor status were identified to be independent predictors of axillary lymph node metastasis (P<0.05 for all). The areas under the ROC curves of the axillary ultrasound model and the comprehensive model were 0.741 (0.684-0.758) and 0.812 (0.767-0.858), respectively. The prediction efficiency of the comprehensive model was greater than that of the axillary ultrasound model (Z=3.5472, P<0.001).

The nomogram developed based on axillary ultrasonic features combined with clinicopathological indicators of breast cancer can improve the diagnostic efficiency for axillary lymph nodes metastasis, and provide effective reference for the staging, prognosis, and treatment of breast cancer.

To compare the diagnostic value of full-field digital mammography (FFDM), automated breast ultrasound (AB US), and contrast-enhanced magnetic resonance imaging (MRI) in breast lesions with architectural distortion (AD).

A retrospective analysis was performed on the clinical, imaging, and pathological data of 171 lesions diagnosed as having AD on FFDM from January 2015 to December 2019, including 171 patients who underwent AB US examination and 108 patients who underwent contrast-enhanced MRI examination. Surgical or puncture pathological results were used as the gold standard for the diagnosis of the nature (benign or malignant) of the lesions; lesions without pathological results were interpreted as benign when there were no changes in imaging features after ≥2 years of follow-up. The diagnostic efficacy of FFDM, AB US, and contrast-enhanced MRI was calculated. Meanwhile, the retraction phenomenon on the coronal plane of AB US was analyzed.

A total of 171 cases were enrolled, of which 143 had pathological results, including 81 malignant and 62 benign lesions. The remaining 28 cases were proved to be benign by follow-up. The proportion of malignant cases with the retraction phenomenon on the coronal plane of AB US was 80.2% (65/81), which was significantly higher than that [45.6% (41/90)] in benign cases (P<0.001). The differences in specificity among FFDM, AB US, contrast-enhanced MRI, and FFDM combined with AB US (17.78% vs 37.77% vs 49.06% vs 47.78%) were statistically significant (P<0.05), but the sensitivity, accuracy, positive predictive value, and negative predictive value had no significant difference (P>0.05).

AB US combined with FFDM could improve the diagnostic efficacy for breast lesions with AD on FFDM. Negative breast MRI findings in such patients may have help avoid unnecessary interventions.

To evaluate the value of ultrasonic high-definition micro-flow imaging (HD-MFI) in differentiating benign and malignant breast masses.

This was a prospective study in which all the patients were enrolled from the First Medical Center, Chinese PLA General Hospital from March 2022 to June 2022, with all masses classified as breast imaging reporting and data system (BI-RADS) 3-5 categories and confirmed by pathology. The blood flow of all masses was evaluated by color Doppler flow imaging (CDFI) and HD-MFI, respectively, and the microvascular patterns (avascular, linear, tree-like, root hair-like, and crab claw-like) of all the masses were assessed by HD-MFI. The detection of blood flow between benign and malignant masses by CDFI and HD-MFI was compared respectively, as well as the differences in microvascular patterns detected by HD-MFI. The diagnostic efficacy of CDFI and HD-MFI in the diagnosis of breast masses was assessed and compared by receiver operating characteristic (ROC) curve analysis.

A total of 114 patients with 119 breast masses were enrolled in this study, and there were 71 benign and 48 malignant masses. More Alder's grade 3 blood flow signals were detected by HD-MFI than by CDFI (72.3% vs 20.1%). On HD-MFI, both benign and malignant breast masses were mostly displayed as Alder's grades 2 and 3, and the proportion of grade 3 malignancies was higher than that of benign masses (85.4% vs 63.4%, P<0.05). Avascular, line-like, and tree-like microvascular patterns were more frequently seen in benign masses by HD-MFI, while root hair-like and crab claw-like patterns were more frequent in malignant masses (P<0.05). The diagnostic specificity (91.5% vs 81.7%), accuracy (86.6% vs 82.4%), positive predictive value (PPV) (86.4% vs 75.5%), and area under the curve [0.854 (0.777~0.912) vs 0.825 (0.745~0.889)] of HD-MFI were higher than those of CDFI.

HD-MFI is a more sensitive technique in detecting blood flow of breast masses in comparison with CDFI. HD-MFI could provide more blood flow information in differentiating benign and malignant breast masses through microvascular patterns.

To assess the predictive value of ultrasonography, mammography, and progesterone receptor (PR) and human epidermal growth factor 2 (HER-2) status for high-grade and middle-low-grade ductal carcinoma in situ (DCIS) of the breast.

A retrospective analysis was performed on 196 patients with breast DCIS confirmed by surgical pathology from January 2015 to December 2020 at Shanxi Tumor Hospital. All patients were examined by ultrasonography and mammography before operation, and had complete pathological data. According to postoperative pathological results, the patients were divided into a high-grade DCIS group (n=80) and a middle-low-grade DCIS group (n=116). Univariate analysis was used to compare the differences in imaging and immunohistochemical features of patients in the two groups. Factors with statistically significant differences in the univariate analysis were included in multivariate Logistic regression analysis to analyze the independent predictors of high-grade and middle-low-grade DCIS.

The statistically significant parameters identified in the univariate analysis, such as mass on ultrasound, microcalcification on mammography, and estrogen receptor (ER), PR, and HER-2 status, were included in binary logistic regression for multivariate analysis. The results showed that mass (odds ratio [OR]=0.248, 95% confidence interval [CI]:0.109～0.562) and PR positivity (OR=0.230, 95%CI:0.057~0.931) were independent predictor of middle-low-grade DCIS. Microcalcification (OR=4.048,95%CI:1.736~9.440) and HER-2 positivity (OR=6.160, 95%CI:2.149~17.655) were identified to be independent predictor of high-grade DCIS.

Preoperative imaging examination and immunohistochemical determination of PR and HER-2 status have appreciated clinical value for the prediction of DCIS and the management and treatment of DCIS patients.

To explore the ultrasound characteristics of breast metaplastic carcinoma containing squamous cell carcinoma components (MCSC) and compare them with pathological results.

Nine patients with MCSC confirmed by surgical and pathological examination at Hubei Cancer Hospital were retrospectively selected. Color Doppler ultrasound was used to scan both the breasts and armpits to observe the ultrasound characteristics of the tumors. BI-RADS classification and Adler blood flow grading were performed on the breast tumors. All MCSC patients underwent gross, microscopic, and immunohistochemical examinations after surgery, and the ultrasound features of the tumors were compared with pathological results.

There were 3 cases of squamous cell carcinoma, 1 case of adenosquamous carcinoma, 1 case of metaplastic carcinoma with mesenchymal differentiation, and 4 cases of mixed metaplastic carcinoma. The maximum diameter of the tumors ranged from 1.07-15.00 cm, with a median diameter of 4.48 cm. Five cases showed mixed internal echoes, and 4 showed hypoechogenicity; 9 showed varying degrees of enhancement in posterior echoes; 7 had unclear or unclear boundaries; 8 had an irregular morphology; 3 were accompanied by calcification. Ultrasound examination showed 4 cases of axillary lymph node enlargement. According to Adler blood flow grading, 8 cases were classified as Grade III, and 1 was classified as Grade I. BI-RADS grading suggested category 4b in 1 case and categories 4c-5 in the remaining. Postoperative pathological examination of gross specimens showed cysts of varying sizes in 8 cases, with only 1 case showing no cysts. Immunohistochemistry showed that there were 4 cases (4/9) of triple negative breast cancer.

Mixed metaplastic carcinoma is the most common type in MCSC, and ultrasound imaging shows the appearance of a malignant tumor. The ultrasound features of a larger tumor volume, mixed echoes with enhanced posterior echoes, and abundant blood supply in the tumor parenchyma are meaningful for the diagnosis of MCSC.

To assess the value of preoperative percutaneous contrast-enhanced ultrasound (CEUS) in the diagnosis of axillary sentinel lymph node (SLN) metastasis in breast cancer and the value of enhancement mode in diagnosing axillary lymph node burden.

Seventy-five breast cancer patients at the Breast Surgery Department of Harbin Medical University Cancer Hospital were enrolled from July 2020 to December 2021. Preoperative percutaneous CEUS was used to identify SLNs and record their enhancement pattern (divided into type Ⅰ uniform enhancement, type Ⅱ non-uniform enhancement, and type Ⅲ no enhancement). Pathological diagnosis was used as the gold standard. The value of enhancement pattern analysis in diagnosing axillary SLN metastasis and burden was then assessed by fourfold table.

The detection rate of CEUS for SLN in 75 breast cancer patients was 97.3% (73/75), and a total of 88 SLNs were detected. Among them, there are 40 type Ⅰlymph nodes, 42 type Ⅱ lymph nodes, and 6 type Ⅲ lymph nodes. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of CEUS enhancement patterns in predicting SLN metastasis were 100%, 62.5%, 50%, 100%, and 72.7%, respectively. Twenty-four of 71 patients with stage T1/T2 breast cancer had sentinel lymph node metastasis, of whom 6 had high lymph node load and 18 had low lymph node load. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the enhancement patterns of CEUS in diagnosing SLN burden status were 100%, 56.9%, 60.6%, 17.6%, and 100%, respectively.

Percutaneous CEUS is effective in identifying axillary SLNs, and CEUS enhancement patterns can help predict axillary SLN metastasis and burden.

To evaluate the value of contrast-enhanced ultrasonography in the diagnosis of male breast masses.

A retrospective study was performed on the medical records of 6 male patients with breast masses diagnosed at the Affiliated Hangzhou Chest Hospital of Zhejiang University School of Medicine from January 2014 to October 2020. All patients were finally diagnosed by pathological results.

All 6 cases of male breast masses were unilateral. Pathology confirmed 3 cases of invasive ductal carcinoma and 3 cases of male breast hyperplasia. Convention ultrasound showed that all the 6 breast masses were hypoechoic. Blood flow signals can be detected in 3 cases of breast cancer, including 2 cases with coarse twisted blood vessels and 1 case with multiple microcalcifications in breast cancer. No microcalcification was found in 1 of 3 cases of breast hyperplasia. Contrast-enhanced ultrasonography revealed that 3 cases of male breast cancer showed uneven enhancement and perfusion defect, but breast hyperplasia did not have this characteristic. Three cases of breast cancer and two cases of breast hyperplasia had expanded enhancement range on contrast-enhanced ultrasound compared to the lesion range detected by conventional ultrasound, while the enhancement range of 1 case of breast hyperplasia was unclear.

Male breast hyperplasia and male breast cancer have different contrast characteristics. Contrast-enhanced ultrasound features such as uneven enhancement and perfusion defect show potential diagnostic value for male breast cancer, which can provide more diagnostic information for clinicians.

To explore the feasibility and clinical value of ultrasound-guided aspiration combined with 50% hypertonic glucose flushing in the treatment of subcutaneous effusion in patients with breast cancer after radical mastectomy.

A retrospective analysis was performed on 89 patients who underwent unilateral radical mastectomy or modified radical mastectomy at Ningbo Hwamei Hospital of the University of Chinese Academy of Sciences from January 2019 to March 2021, and had subcutaneous effusion after extubation after surgery. The patients were completely randomly divided into a conventional aspiration group (31 cases), an ultrasound-guided aspiration group (28 cases), and an ultrasonic-guided aspiration +50% hypertonic glucose flushing group (30 cases). The total amount of fluid aspirated, the number of punctures in the hospital, and the healing time were compared among the three groups by one-way analysis of variance, and pairwise comparisons between groups were performed using the SNK test.

The total amount of fluid aspirated, the number of punctures, and the healing time were (41.31±12.36) ml, (2.83±0.79) times, and (15.37±2.75) d, respectively, in the ultrasound-guided aspiration combined with hypertonic glucose flushing group, which were significantly lower than those in the conventional aspiration group [(50.67±12.10) ml, (4.61±1.12) times, and (26.39±4.98) d, respectively; P<0.05] and the ultrasound-guided aspiration group [(44.69±15.72) ml, (3.36±1.25) times, and (19.00±2.09) d, respectively; P<0.05].

Ultrasound-guided aspiration combined with 50% hypertonic glucose flushing is effective in the treatment of subcutaneous effusion in patients with breast cancer after radical mastectomy, and it reduces the pain of patients and shortens the treatment time.