Predicting postoperative malignancy upgrading in B1–B3 breast lesions: combined utility of conventional ultrasound and contrast-enhanced ultrasound features

Introduction

Conventional ultrasound (US)-guided core needle biopsy (CNB) is routinely employed as a standard, safe, and cost-effective method for preoperative pathological evaluation of US-visualized breast lesions (1,2). Pathological results for CNB were defined as five categories: B1: normal or non-diagnostic tissue; B2: benign lesion; B3: benign lesion with unknown biological potential; B4: suspicious for malignancy; B5: malignant (3,4). However, regardless of the biopsy needle gauge, CNB results are susceptible to false negatives or underestimation due to sampling errors, tumor heterogeneity, and overlapping histopathological features (1,5). The reported total malignancy missing rate of B1 and B2 lesions was 3%, while the underestimation of malignancy for B3 lesions was approximately 10–35% (6,7). To enhance the accuracy of preoperative CNB diagnosis for breast lesions, representative tumor regions must be targeted for sampling. Furthermore, radiologic-pathologic concordance evaluation can be crucial for B1–B3 lesions (2,5). Radiologic-pathologic discordance has been defined as cases where breast lesions classified as Breast Imaging Reporting and Data System (BI-RADS) category 4 or 5 (specifically BI-RADS 4B, 4C, and 5) on imaging are diagnosed as uncertain or benign on histopathological examination (8,9). However, this can be confusing due to the overlapping imaging features of benign and malignant lesions and the lack of objective criteria for BI-RADS 4 subcategorization (10). Therefore, identifying features suggestive of malignancy in B1–B3 lesions to avoid treatment delays is of great interest.

Contrast-enhanced ultrasound (CEUS) reveals tumor neovascularization and perfusion using non-renally excreted US contrast agents (11,12). It can help identify appropriate biopsy targets by visualizing active and necrotic areas, thereby enhancing the accuracy of preoperative CNB diagnosis (13,14). Furthermore, qualitative and quantitative CEUS features have been proven useful in differentiating benign and malignant breast lesions and in evaluating the response to neoadjuvant chemotherapy (15-17). Previous studies have also shown that the supplementary application of CEUS can be beneficial in predicting the upgrade of ductal carcinoma in situ (DCIS) and atypical ductal hyperplasia (18,19). Nevertheless, it remains unknown whether conventional US combined with CEUS could aid in identifying high-risk B1–B3 lesions potentially upstaged to malignancy during surgery.

In short, this study aimed to explore the role of conventional US and CEUS features in postoperative malignancy upgrading of category B1–B3 lesions diagnosed by CEUS-guided CNB. We present this article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2678/rc).

Methods

Patients

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the institutional review board of Nanjing Drum Tower Hospital (approval No. 2025-007-01) and individual consent for this analysis was waived due to its retrospective nature. Informed consent for CEUS, CNB, and surgery was obtained from all the patients.

Patients with suspicious breast lesions with a BI-RADS assessment of 4A or higher were reviewed between February 2023 and February 2025. Inclusion criteria were that patients (I) underwent US examination, CEUS examination, CEUS-guided CNB and surgical resection in Nanjing Drum Tower Hospital; (II) had available histopathology results from both biopsy and surgical specimens; (III) had biopsy results classified as B1–B3 lesions. Exclusion criteria were (I) history of biopsy, resection, or treatment of lesions before CEUS-guided CNB; (II) intervals between CEUS-guided CNB and surgical resection exceeding 2 weeks; and (III) unsatisfactory or unavailable conventional US or CEUS image quality. Ultimately, 84 lesions in 79 female patients [median age 44.00 (interquartile range, 37.00–50.75) years, range, 26–81 years] were enrolled in this study. The participant selection flowchart is shown in Figure 1.

Figure 1 A flowchart indicating inclusion and exclusion criteria. CEUS, contrast-enhanced ultrasound; CNB, core needle biopsy; n, number; pn, patient number; US, ultrasound.

Instruments and materials

Conventional US, CEUS, and biopsy were performed using a Mindray Resona R9T system (Mindray, Shenzhen, China) with a L9-3U linear transducer (mechanical index: 0.06–0.08). The contrast agent used in this study was SonoVue (Bracco, Milan, Italy). The CEUS time intensity curves (TICs) were acquired by Mipangu (Mindray). A 16-gauge semiautomatic biopsy instrument (Gallini Medical, Mantova, Italy) equipped with a coaxial introducer needle was chosen for each biopsy, based on lesion characteristics.

Imaging acquisition and interpretation

After complete exposure of the lesions, conventional US was performed. A sonographer (H.H.), with over 15 years of experience in breast imaging, obtained optimal conventional US images. Blinded to patient information, two independent sonographers (Y.L.Z. and W.K.J.), with 3 and 10 years of breast imaging experience, respectively, independently evaluated the lesions’ conventional US features. Disagreements were resolved through discussion under the supervision of a senior sonographer (H.H.). Criteria for interpretation were based on previous literature (19-21). The following features were recorded: (I) size (maximum diameter on conventional US: ≤20 mm; >20 mm); (II) shape (regular; irregular); (III) margin (circumscribed; non-circumscribed); (IV) orientation: (parallel; non-parallel); (V) posterior acoustic effect (unaltered or enhanced; attenuation); (VI) microcalcification (absent; present); (VII) high vascularity (Adler blood flow grade II–III: absent; present); (VIII) peritumoral ductal dilation (absent; present); and (IX) abnormal lymph nodes (absent; present).

After the conventional US examination, CEUS imaging was performed by H.H. Prior to injection of SonoVue, 5 mL of saline was administered and shaken to create a microbubble suspension. CEUS examination was performed following an intravenous injection of 4.8 mL of microbubble at the start of the built-in timer of the US instrument, followed by 5 mL of saline. To facilitate dual imaging, a split screen was employed, allowing one screen to display the conventional US and the other to show CEUS images. Continuous imaging was conducted, and the perfusion details were documented in a video recording for a duration of 2 minutes into the instrument’s hard disk for further quantitative analyses. Criteria for qualitative analysis of CEUS were based on previous literature and our clinical experience (18,22-24). The following features were recorded: (I) wash-in time (later or synchronous; earlier); (II) enhancement distribution (homogeneous; heterogeneous); (III) enhancement intensity (hypo- or iso-enhancement; hyper-enhancement); (IV) enhancement margin (circumscribed or non-circumscribed); (V) enhancement range (an increase of ≥3 mm in length or width compared with conventional US: non-enlarged; enlarged); (VI) contrast agent retention (absent; present); (VII) penetrating vessels (absent; present); (VIII) perfusion defects (absent; present); and (IX) enhancement direction (non-centripetal; centripetal).

For CEUS quantitative analyses, Y.L.Z. and W.K.J. independently drew a region of interest (ROI) for each lesion. The ROIs were manually drawn according to the lesion margin and shape observed on conventional US. Subsequently, the automatic adaptive contouring function was employed to create a peritumoral ROI extending 2 mm beyond the lesion margin. The TICs for both the intratumoral and peritumoral ROIs were then automatically generated. The following quantitative features for intratumoral ROIs were recorded: (I) mean TIC (mTIC): mean intensity of TIC; (II) peak intensity (PkI); (III) arrival time (AT): the time point on the TIC corresponding to a 10 dB increase from baseline; (IV) rising time (RT); (V) time to peak (TTP); (VI) ascending slope (AS); (VII) descending slope (DS); (VIII) falling time (FT); (IX) mean transition time (mTT). The mTIC, PkI, and TTP for peritumoral ROIs were recorded as well. To mitigate inter-observer variability, the measurements from Y.L.Z. and W.K.J. were averaged to yield the final results.

Biopsy procedures

The CEUS-guided CNB was performed by H.H. The areas with hyper-enhancement on CEUS were identified as the target areas. Due to the low spatial and temporal resolution of the contrast-enhanced model (14), all the biopsy procedures were performed under the real-time guidance of conventional US. A total of 4–5 biopsy samplings were obtained by CEUS-guided CNB. The specimens were immediately placed in a 10% neutral buffered formalin solution and underwent fixation and staining following the standard pathological procedure.

Histopathological evaluation

Histopathological results for both CNB and surgical excision were categorized as B1 to B5 (3,4). Postoperative malignancy upgrading was defined as a case where the initial biopsy yielded a B1–B3 classification, but the surgical pathology showed a B5 classification.

Statistical analysis

Statistical analyses were performed with SPSS 26.0 software (IBM, Ehningen, Germany). The Shapiro-Wilk analysis was performed to assess normal distributions. Continuous variables were reported as mean ± standard deviation or median with an interquartile range (25%, 75%) depending on whether they were normally distributed. Inter-observer agreement for conventional US and CEUS evaluations was assessed by intraclass correlation coefficient (ICC) analysis. An ICC >0.80 indicated excellent consistency between observers (14). To compare the differences in conventional US and CEUS features between upgrading group and non-upgrading group, the χ² or Fisher’s exact tests were applied for the comparisons of qualitative features. Independent-sample t-test (for normally distributed data) and Mann-Whitney U test (for data with non-normal distribution) were employed for the comparisons of quantitative features. Features that achieved significance in the uni-variable analysis were entered into multi-variable logistic regression analysis to identify independent predictors of postoperative upgrading. Binary logistic regression method was used to combine the identified independent predictors to construct the multi-variable model. A non-significant Hosmer-Lemeshow test (P>0.05) indicated good fit for the multi-variable logistic regression model. Receiver operating characteristic (ROC) curve analysis was used to assess the predictive ability of independent predictors and their combinations with respect to postoperative upgrading. Areas under the curves (AUCs) were calculated. DeLong test was used to compare the efficiency of different models. A two-sided P<0.05 was indicative of a statistically significant difference.

Results

Basic characteristics

A total of 71 lesions were recruited in the non-upgrading group, with 47 (66.20%) lesions classified as B2 category and 24 (33.80%) lesions classified as B3 category by surgical histopathology. The median age was significantly higher in lesions with upgrading than those without upgrading [54.00 (interquartile range, 50.50, 62.50) vs. 43.00 (interquartile range, 36.00, 47.00) years, P<0.001]. In the upgrading group, 13 lesions were recruited with 1 (7.69%) lesion classified as B1, 2 (15.38%) lesions classified as B2 category and 10 (76.92%) lesions classified as B3 category by biopsy histopathology. Histopathological results for both biopsy and surgery of the upgrading group are summarized in Table 1. No biopsy complications were identified in any enrolled patients.

Uni-variable analysis

The inter-observer agreement of conventional US and CEUS features in the non-upgrading and upgrading groups was excellent (ICC >0.80), as shown in Tables 2,3. Uni-variable comparisons of detailed conventional US features and CEUS features between the two groups are displayed in Tables 2,3. Only one conventional US feature, size, was found to be significantly different between the two groups (P=0.023). The qualitative CEUS feature, enhancement range, was significantly different between the two groups (P=0.002). No significantly discriminatory quantitative CEUS features were found, although peritumoral mTIC approached statistical significance (P=0.083).

Multi-variable analysis

On the basis of multi-variable analysis, size >20 mm on conventional US [odds ratio (OR) =5.85; 95% confidence interval (CI): 1.49–22.92; P=0.011] and enlarged enhancement range on CEUS (OR =17.44; 95% CI: 2.03–150.02; P=0.009) were identified as independent predictors for postoperative pathological upgrading. A multi-variable model was constructed using both independent predictors, with the formula: logit (P) = 1.767 × size + 2.859 × enhancement range − 4.541. The Hosmer-Lemeshow test indicated the absence of statistical significance (P=0.788). Figures 2,3 show images representative cases from the non-upgrading and upgrading groups.

Figure 2 Images of a representative case in the non-upgrading group. A 30-year-old female patient presented with a BI-RADS 4A lesion in the left breast. Both the biopsy and surgical results were classified as B3 (intraductal papilloma). (A,B) Conventional US images showed a 12 mm × 9 mm lesion with an irregular shape, circumscribed margin, parallel orientation, unaltered posterior acoustic effect, absence of microcalcification and no high vascularity. In (B), the box indicates the Doppler sampling frame. (C,D) The images showed the intratumoral and peritumoral ROIs (inner dashed-line area and area between the outer and inner dashed lines, respectively) on CEUS. There was a non-enlarged enhancement range of this lesion. BI-RADS, Breast Imaging Reporting and Data System; CEUS, contrast-enhanced ultrasound; ROI, region of interest; US, ultrasound.

Figure 3 Images of a representative case in the upgrading group. A 67-year-old female patient presented with a BI-RADS 4C lesion in the right breast. The biopsy result was classified as B3 (intraductal papilloma) and surgical result was classified as B5 (invasive carcinoma with encapsulated papillary carcinoma). (A,B) Conventional US images showed a 21 mm × 15 mm lesion with an irregular shape, non-circumscribed margin, parallel orientation, unaltered posterior acoustic effect, absence of microcalcification and high vascularity. In (B), the box indicates the Doppler sampling frame. (C,D) The images showed the intratumoral and peritumoral ROIs (inner dashed-line area and area between the outer and inner dashed lines, respectively) on CEUS. There was an enlarged enhancement range of this lesion. BI-RADS, Breast Imaging Reporting and Data System; CEUS, contrast-enhanced ultrasound; ROI, region of interest; US, ultrasound.

ROC curve analysis was used to evaluate the predictive performance of size >20 mm on conventional US, enlarged enhancement range on CEUS, and the multi-variable model (size >20 mm on conventional US + enlarged enhancement range on CEUS), as shown in Figure 4. The sensitivity, specificity, and AUC of size >20 mm on conventional US for predicting postoperative pathological upgrading were 61.54%, 74.65%, and 0.68 (95% CI: 0.57–0.78), respectively. The sensitivity, specificity, and AUC of enlarged enhancement range on CEUS were 92.31%, 54.93% and 0.74 (95% CI: 0.63–0.83), respectively. The largest AUC of 0.83 (95% CI: 0.73–0.90) was obtained by multi-variable model, and the sensitivity and specificity were 92.31% and 54.93%, respectively, demonstrating significantly better performance than size >20 mm (P=0.027) and enlarged enhancement range (P=0.013).

Figure 4 ROC curve analyses of independent predictors and their combinations for predicting postoperative malignancy upgrading. (A) ROCs of size >20 mm on conventional US, enlarged enhancement range on CEUS, and the multi-variable model. (B) Confusion matrix of the multi-variable model. BI-RADS, Breast Imaging Reporting and Data System; CEUS, contrast-enhanced ultrasound; ROC, receiver operating characteristic; US, ultrasound.

Discussion

Lesions diagnosed as category B1–B3 by CNB can be overlooked clinically because their pathology results do not explicitly indicate malignancy (3). Given the potential for underestimation of malignancy by CNB, a radiologic-pathologic concordance assessment is crucial for these lesions to avoid inappropriate management. To address this potential underestimation, our study investigated conventional US and CEUS features predictive of malignancy upgrade in B1–B3 lesions diagnosed via CEUS-guided CNB, which may help to optimize clinical decision-making.

In this study, the overall malignancy upgrading rate was 15.48%, with 4.08% for B2 lesions and 29.41% for B3 lesions. The observed upgrading rate for B2 lesions was modestly higher than that previously reported, while the upgrading rate for B3 lesions was consistent with prior findings (6,7,25). The slight discrepancy may be attributed to variations in the study populations. In addition, one B1 lesion was observed in our study. This suggested that, although CEUS was useful in identifying necrotic areas with filling defects and guiding CNB targeting, insufficient sample acquisition due to tumor heterogeneity still existed.

Size >20 mm on conventional US was found to be significantly associated with the upgrade of B1–B3 lesions. This finding aligned with the observation that malignant lesions tended to be significantly larger than benign ones (26). Larger size may indicate greater intratumoral heterogeneity, potentially leading to sampling errors during CNB and an increased likelihood of missing malignant components (27). Nonetheless, previous studies mainly focused on the upgrade of DCIS. Zhu et al. (18) and Brennan et al. (28) both found that lesion size larger than 20 mm at imaging was significantly associated with understaging for DCIS at CNB. Recently, a multi-center study reported that lesion size >15 mm was predictive of upgrading in B3 lesions at CNB (29), but this size threshold differed from the one we used.

Qualitative and quantitative CEUS features of lesions were analyzed in our study, with the enlarged enhancement range serving as an independent predictive factor for malignancy upgrading. The progression and development of breast cancer can be characterized by rich and abnormal angiogenesis, which is undetectable on conventional US. However, CEUS can enhance the visualization of intratumoral and peritumoral microvascular perfusion, revealing tumor margins and infiltrative areas that contribute to the observed enlarged enhancement range (30). Our findings also indicated that the combination of the above two predictive features can help efficiently identify lesions that were at a high risk of pathological upgrade, with an AUC value of 0.83.

What is more, we conducted quantitative CEUS analysis not only on the lesion itself but also on the peritumoral 2-mm region. Nevertheless, no statistically significant features were found. Similarly, many studies have shown that quantitative features were less effective than qualitative features in predicting malignancy in breast lesions (31). The peritumoral 2-mm region of lesions in the upgrading group tended to have a higher mTIC, but this difference was not statistically significant. Given the small sample size, definitive conclusions regarding this trend cannot be drawn. It was important to emphasize that the features derived from quantitative analyses were susceptible to a multitude of intrinsic and extrinsic confounding factors, such as cardiac output or vascular elasticity (32). The quantitative analyses of the lesion and peritumoral region as single entities may obscure regional heterogeneity, potentially influencing the overall findings (32).

This study had certain limitations. First, as a single-center, retrospective analysis, the sample size may have introduced selection bias. Further large-scale, prospective, multi-center trials are necessary to validate our findings. Second, several important qualitative and quantitative features were excluded from the analysis due to poor inter-observer agreement, such as the shape assessment of iso-enhanced lesions on CEUS. Third, a detailed subgroup analysis was not performed. The literature showed distinct CEUS characteristics across lesion pathological subtypes and molecular subtypes (33,34). For example, perfusion defects and peripheral high enhancement were more frequently associated with DCIS than with invasive carcinoma (33). Consequently, our reported overall diagnostic performance may average out these differences. Finally, although a statistically significant age difference was observed between the two groups in our study, relevant clinical characteristics were not incorporated into the predictive model. This was because this study focused on the role of conventional US and CEUS in predicting postoperative malignancy upgrading. Future research should incorporate additional clinical and imaging features to refine the predictive model.

Conclusions

In conclusion, the combination of conventional US and CEUS features can be helpful in predicting postoperative malignancy upgrading for B1–B3 lesions diagnosed by CEUS-guided CNB. This approach may refine clinical management, reducing delays in treatment for high-risk cases.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2678/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2678/dss

Funding: This work was supported by Nanjing Medical Science and Technology Development Fund (No. YKK21102 to H.H.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2678/coif). H.H. reports funding from Nanjing Medical Science and Technology Development Fund (No. YKK21102). The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the institutional review board of Nanjing Drum Tower Hospital (approval No. 2025-007-01) and individual consent for this analysis was waived due to its retrospective nature.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Huang ML, Hess K, Candelaria RP, Eghtedari M, Adrada BE, Sneige N, Fornage BD. Comparison of the accuracy of US-guided biopsy of breast masses performed with 14-gauge, 16-gauge and 18-gauge automated cutting needle biopsy devices, and review of the literature. Eur Radiol 2017;27:2928-33. [Crossref] [PubMed]
2. Bick U, Trimboli RM, Athanasiou A, Balleyguier C, Baltzer PAT, Bernathova M, et al. Image-guided breast biopsy and localisation: recommendations for information to women and referring physicians by the European Society of Breast Imaging. Insights Imaging 2020;11:12. [Crossref] [PubMed]
3. Perry N, Broeders M, de Wolf C, Törnberg S, Holland R, von Karsa L. European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition--summary document. Ann Oncol 2008;19:614-22.
4. Mohrmann S, Maier-Bode A, Dietzel F, Reinecke P, Krawczyk N, Kaleta T, Kreimer U, Antoch G, Fehm TN, Roth KS. Malignancy Rate and Malignancy Risk Assessment in Different Lesions of Uncertain Malignant Potential in the Breast (B3 Lesions): An Analysis of 192 Cases from a Single Institution. Breast Care (Basel) 2022;17:159-65. [Crossref] [PubMed]
5. Giuliani M, Rinaldi P, Rella R, Fabrizi G, Petta F, Carlino G, Di Leone A, Mulè A, Bufi E, Romani M, Belli P, Bonomo L. Effect of Needle Size in Ultrasound-guided Core Needle Breast Biopsy: Comparison of 14-, 16-, and 18-Gauge Needles. Clin Breast Cancer 2017;17:536-43. [Crossref] [PubMed]
6. Rakha EA, Lee AH, Reed J, Murphy A, El-Sayed M, Burrell H, Evans AJ, Ellis IO. Screen-detected malignant breast lesions diagnosed following benign (B2) or normal (B1) needle core biopsy diagnoses. Eur J Cancer 2010;46:1835-40. [Crossref] [PubMed]
7. Giannotti E, James JJ, Chen Y, Sun R, Karuppiah A, Yemm J, Lee AHS. Effectiveness of percutaneous vacuum-assisted excision (VAE) of breast lesions of uncertain malignant potential (B3 lesions) as an alternative to open surgical biopsy. Eur Radiol 2021;31:9540-7. [Crossref] [PubMed]
8. Vatteroni G, Pinna G, Trimboli RM, Levi R, Bolengo I, Patrone F, Volpe D, Fernandes B, Bernardi D. Role of ultrasound-guided vacuum-assisted breast biopsy in the management of radiologic-pathologic discordance: a retrospective single-centre study. Radiol Med 2024;129:1454-62. [Crossref] [PubMed]
9. Youk JH, Kim EK, Kim MJ, Ko KH, Kwak JY, Son EJ, Choi J, Kang HY. Concordant or discordant? Imaging-pathology correlation in a sonography-guided core needle biopsy of a breast lesion. Korean J Radiol 2011;12:232-40. [Crossref] [PubMed]
10. Jörg I, Wieler J, Elfgen C, Bolten K, Hutzli C, Talimi J, Vorburger D, Choschzick M, Moskovszky L, Dedes K, Varga Z. Discrepancies between radiological and histological findings in preoperative core needle (CNB) and vacuum-assisted (VAB) breast biopsies. J Cancer Res Clin Oncol 2021;147:749-54. [Crossref] [PubMed]
11. Zhou SC, Le J, Zhou J, Huang YX, Qian L, Chang C. The Role of Contrast-Enhanced Ultrasound in the Diagnosis and Pathologic Response Prediction in Breast Cancer: A Meta-analysis and Systematic Review. Clin Breast Cancer 2020;20:e490-509. [Crossref] [PubMed]
12. Sidhu PS, Cantisani V, Dietrich CF, Gilja OH, Saftoiu A, Bartels E, et al. The EFSUMB Guidelines and Recommendations for the Clinical Practice of Contrast-Enhanced Ultrasound (CEUS) in Non-Hepatic Applications: Update 2017 (Long Version). Ultraschall Med 2018;39:e2-e44. [Crossref] [PubMed]
13. Wu W, Jing X, Xue GQ, Zhu XL, Wang J, Du RQ, Lv B, Wang KF, Yan JP, Zhang ZY, Li MD, Kono Y, Yan K. A Multicenter Randomized Controlled Study of Contrast-enhanced US versus US-guided Biopsy of Focal Liver Lesions. Radiology 2022;305:721-8. [Crossref] [PubMed]
14. Zhang YL, Wu MJ, Hu Y, Ma Q, Wei ZK, Yao QY, Huang YM, Li A. Contrast-enhanced ultrasound guided core needle biopsy for soft tissue tumors: Accuracy and applicability. Eur J Radiol 2023;168:111114. [Crossref] [PubMed]
15. Niu Q, Zhao L, Wang R, Du L, Shi Q, Jia C, Li G, Jin L, Li F. Predictive value of contrast-enhanced ultrasonography and ultrasound elastography for management of BI-RADS category 4 nonpalpable breast masses. Eur J Radiol 2024;173:111391. [Crossref] [PubMed]
16. Wang B, Yang D, Zhang X, Gong X, Xu T, Han J, Ren Y, Zou S, Li L, Wang Y. The diagnostic value of contrast-enhanced ultrasonography in breast ductal abnormalities. Cancer Imaging 2023;23:25. [Crossref] [PubMed]
17. Xiao X, Jiang Q, Wu H, Guan X, Qin W, Luo B. Diagnosis of sub-centimetre breast lesions: combining BI-RADS-US with strain elastography and contrast-enhanced ultrasound-a preliminary study in China. Eur Radiol 2017;27:2443-50. [Crossref] [PubMed]
18. Zhu Y, Jia X, Zhan W, Zhou J. Adding contrast-enhanced ultrasound can improve the predictive ability of breast conventional ultrasound and mammography for pathological upgrade of biopsy-confirmed ductal carcinoma in situ. Eur J Radiol 2024;180:111687. [Crossref] [PubMed]
19. Li JK, Jin ZY, Xu YJ, Fu NQ, Jiang Y, Li SY, Niu RL, Liu G, Wang ZL. Contrast-enhanced ultrasound to predict malignant upgrading of atypical ductal hyperplasia. Breast Cancer Res 2024;26:27. [Crossref] [PubMed]
20. Du Y, Yi CB, Du LW, Gong HY, Ling LJ, Ye XH, Zong M, Li CY. Combining primary tumor features derived from conventional and contrast-enhanced ultrasound facilitates the prediction of positive axillary lymph nodes in Breast Imaging Reporting and Data System category 4 malignant breast lesions. Diagn Interv Radiol 2023;29:469-77. [Crossref] [PubMed]
21. Fang J, Deng Q, Zhang J, Ma Y, Jin C, Lu J, Hao Y, Ma Y, Liu W, Li Z, Liu G, Mo Y, Xiao Y, Zheng C, Yang Y, Wu T, Zhao C, Zhou X, Zhou P. A Nomogram Based on Conventional and Contrast-Enhanced Ultrasound for Pre-operative Prediction of Nipple-Areola Complex Involvement in Breast Cancer: A Prospective Study. Ultrasound Med Biol 2023;49:2565-72. [Crossref] [PubMed]
22. Wu T, Chen J, Shao S, Du Y, Li F, Liu H, Sun L, Diao X, Wu R. Prediction of Microinvasion in Breast Ductal Carcinoma in Situ Using Conventional Ultrasound Combined with Contrast-Enhanced Ultrasound Features: A Two-Center Study. Clin Breast Cancer 2025;25:e178-89. [Crossref] [PubMed]
23. Sun J, Shen X, Zhang N, Zhang Q, Xing K, Liu Y. Combination of conventional ultrasound with quantitative and qualitative analyses of CEUS for the differentiation of benign and malignant breast solid lesions: A modified breast cancer model. Asian J Surg 2024; Epub ahead of print. [Crossref]
24. Jiang Y, Li JK, Huang SS, Li SY, Niu RL, Fu NQ, Wang ZL. The diagnostic value of contrast-enhanced ultrasound combined with clinicopathological features in microinvasive ductal carcinoma in situ. Gland Surg 2024;13:1894-906. [Crossref] [PubMed]
25. Schueller G, Jaromi S, Ponhold L, Fuchsjaeger M, Memarsadeghi M, Rudas M, Weber M, Liberman L, Helbich TH. US-guided 14-gauge core-needle breast biopsy: results of a validation study in 1352 cases. Radiology 2008;248:406-13. [Crossref] [PubMed]
26. Bednarova I, Londero V, Linda A, Girometti R, Lorenzon M, Bednarova S, Zuiani C. Do clinical and radiologic features help predict malignancy of B3 breast lesions without epithelial atypia (B3a)? Radiol Med 2018;123:809-17. [Crossref] [PubMed]
27. Park AY, Son EJ, Kim JA, Han K, Youk JH. Lesion stiffness measured by shear-wave elastography: Preoperative predictor of the histologic underestimation of US-guided core needle breast biopsy. Eur J Radiol 2015;84:2509-14. [Crossref] [PubMed]
28. Brennan ME, Turner RM, Ciatto S, Marinovich ML, French JR, Macaskill P, Houssami N. Ductal carcinoma in situ at core-needle biopsy: meta-analysis of underestimation and predictors of invasive breast cancer. Radiology 2011;260:119-28. [Crossref] [PubMed]
29. Oktay A, Aslan Ö, Taşkın F, Tunçbilek N, Esen İçten SG, Balcı P, et al. Outcomes of high-risk breast lesions diagnosed using image-guided core needle biopsy: results from a multicenter retrospective study. Diagn Interv Radiol 2023;29:579-87. [Crossref] [PubMed]
30. Ishida H, Naganuma H. The Size Differences of Breast Cancer and Benign Tumors Measured by Two-Dimensional Ultrasound and Contrast-Enhanced Ultrasound. J Ultrasound Med 2025;44:589-90. [Crossref] [PubMed]
31. Weng H, Zhao Y, Xu Y, Hong Y, Wang K, Huang P. A Diagnostic Model for Breast Lesions With Enlarged Enhancement Extent on Contrast-Enhanced Ultrasound Improves Malignancy Prediction. Ultrasound Med Biol 2023;49:1535-43. [Crossref] [PubMed]
32. Wang Y, Fan W, Zhao S, Zhang K, Zhang L, Zhang P, Ma R. Qualitative, quantitative and combination score systems in differential diagnosis of breast lesions by contrast-enhanced ultrasound. Eur J Radiol 2016;85:48-54. [Crossref] [PubMed]
33. Li X, Zhang J, Zhang G, Liu J, Tang C, Chen K, Chen P, Tan L, Guo Y. Contrast-Enhanced Ultrasound and Conventional Ultrasound Characteristics of Breast Cancer With Different Molecular Subtypes. Clin Breast Cancer 2024;24:204-14. [Crossref] [PubMed]
34. Li W, Zhao Y, Fei X, Wu Y, Zhan W, Zhou W, Xia S, Song Y, Zhou J. Image Features and Diagnostic Value of Contrast-Enhanced Ultrasound for Ductal Carcinoma In Situ of the Breast: Preliminary Findings. Ultrason Imaging 2025;47:59-67. [Crossref] [PubMed]