The value of multi-parametric ultrasonography nomogram in predicting nipple-areolar complex involvement in breast cancer

Introduction

Breast cancer (BC) is the most commonly diagnosed malignancy in women worldwide, posing a significant threat to global public health (1). Increasingly preferred in BC surgery, nipple-sparing mastectomy (NSM) removes breast tissue while preserving the skin and nipple-areolar complex (NAC), offering patients the combination of excellent cosmetic and oncological outcomes (2,3). Previous studies have reported that, despite a clinically normal NAC on physical examination, NAC involvement can be identified in approximately 16.7% of cases by postoperative pathology (4). Consequently, the primary oncological risk associated with NSM is the potential retention of residual tumor cells within the preserved NAC, which may subsequently lead to local recurrence (5). The literature reports a low incidence of local cancer recurrence after NSM, provided that careful patient selection criteria are applied (6). Therefore, precise assessment of NAC involvement in BC is crucial for appropriate patient management.

Breast magnetic resonance imaging (MRI) is routinely employed for the preoperative evaluation of patients being considered for NSM with higher sensitivity than mammography and conventional ultrasound (CUS) (3). MRI features that have been shown to significantly correlate with NAC include tumor size, multifocality/multicentricity, central location, short tumor-to-nipple distance (TND), ductal enhancement extending to the nipple (DEEN), unilateral NAC enhancement, nipple retraction, and thickening of the NAC (7,8). However, MRI is not suitable for patients with contraindications, such as renal impairment, metal implants, and claustrophobia.

CUS, a common imaging modality, plays an important role in the screening and diagnosis of BC due to its non-invasive, radiation-free nature and low cost (9). Strain elastography (SE) and contrast-enhanced ultrasound (CEUS) have emerged as valuable complements to clinical breast ultrasound. SE identifies pathologies by detecting increased stiffness resulting from calcification, fibrous tissue, or collagen components through variations in tissue elasticity (10). Beyond offering a qualitative visual map of tissue hardness, SE provides a quantitative evaluation using strain rate values (11,12). CEUS provides excellent spatial and temporal resolution to display microcirculatory perfusion, which aids in distinguishing mass lesions, staging invasive cancer, detecting tumor recurrence, and assessing response to neoadjuvant chemotherapy (13,14). Previously, we developed a nomogram combining CUS and CEUS for preoperative prediction of NAC involvement in BC, which show a strong predictive performance, with an area under the curve (AUC) of 0.891 and an overall accuracy of 85.5% (15). Although the combination of SE and CEUS has been shown to be highly valuable in BC diagnosis and therapeutic evaluation, its potential for evaluating malignant involvement of the NAC remains largely unexplored.

In this study, we aimed to compare and evaluate the diagnostic value of combining CUS, SE, and CEUS in predicting NAC involvement in BC, and to establish a relatively objective and clinically practical multi-parametric ultrasonography nomogram for surgical planning. We present this article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2026-1-0142/rc).

Methods

This prospective study was registered with the Chinese Clinical Trial Registry (registration no. ChiCTR2000034240) and approved by the Ethics Committee of The First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People’s Hospital (No. 20200601005). Written informed consent was provided by all study participants. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Study participants

Consecutive female BC patients confirmed by needle biopsy between January 2020 and December 2024 were prospectively enrolled. No patient was preselected based on NAC-related symptoms or signs. The inclusion criteria were as follows: (I) newly diagnosed primary BC confirmed by needle biopsy; (II) willingness to undergo CUS, SE, and CEUS examination before surgery and no contraindications for CEUS; (III) subareolar intraoperative biopsy and postoperative immunohistochemical staining were used to assess NAC involvement; and (IV) duration of ≤1 month between ultrasound examination and surgery. The exclusion criteria were as follows: (I) a history of previous surgery, neoadjuvant chemotherapy, radiation therapy, or endocrine therapy involving the NAC; (II) incomplete and low-quality CUS, SE, and CEUS data; and (III) incomplete operative and postoperative pathological information. The patient selection process, including inclusion and exclusion criteria, is illustrated in Figure 1.

Figure 1 Flowchart of patient selection process. CEUS, contrast-enhanced ultrasound; CUS, conventional ultrasound; NAC, nipple-areolar complex; SE, strain elastography.

CUS, SE, and CEUS examinations

All examinations were conducted following standardized protocols by two radiologists, each having over a decade of experience in breast ultrasound imaging and specific expertise in SE and CEUS. We conducted all ultrasound examinations (CUS, SE, and CEUS) using a GE LOGIQ E9 system (GE Healthcare, Milwaukee, WI, USA), which was equipped with L6–15 (6–15 MHz) and L3–9 (3–9 MHz) linear array transducers. The contrast agent used was Sono Vue (Bracco, Milan, Italy).

Patients were placed in a supine position with both arms elevated and the hands placed beneath the head. The examination was performed with the mechanical index set between 0.18 and 0.22, and with the focus, gain, and depth appropriately adjusted. A thorough CUS scan was performed to image the lesion and nipple simultaneously in the radial plane. For color Doppler assessment, minimal compression was applied while performing multi-planar and multi-angle scanning. Both grayscale and color Doppler characteristics were recorded. For patients with multiple lesions, the lesion closest to the NAC was selected for analysis; for those with non-mass lesions, the area displaying the most conspicuous diffuse calcifications or the most marked architectural distortion was deemed representative and selected.

Furthermore, elasticity images were acquired using SE in dual-display mode. Sampling boxes were placed to contain the nipple, lesions, and sufficient surrounding normal parenchyma. With stable pre-compression, the transducer was oriented perpendicularly and then gently oscillated to produce subtle tissue deformation. A relatively stable elastogram was captured when the color frame displayed green and full, indicating a stable pressure curve.

Lastly, following the acquisition of clear CUS and SE images, the dual-screen CEUS mode was activated to capture the enhancement characteristics. A radial imaging plane simultaneously encompassing both the lesion and the nipple was selected as the target section. Standardized settings included a low mechanical index of 0.06 for all participants to avoid microbubble disruption and to maintain stable contrast enhancement for low-velocity blood flow detection, with the focus placed at the deepest margin of the lesion. Minimal transducer pressure was maintained to avoid vascular compression. A 4.8 mL bolus of SonoVue contrast agent was administered intravenously via the antecubital vein, followed by a 5 mL saline flush. Dynamic imaging commenced at the start of injection and was continuously recorded for 120 seconds for subsequent analysis.

Image interpretation

The CUS, SE, and CEUS images were reviewed independently by two senior radiologists who were blinded to all clinical and pathological data. Any discrepancies between their assessments were resolved through consultation with a third senior radiologist to reach a consensus. CUS images were read according to the 5th edition of the American College of Radiology Breast Imaging Reporting and Data System ultrasound lexicon (16). The following CUS characteristics were recorded: tumor size, TND, location, lesion type, shape, orientation, margin, echo pattern, internal homogeneity, microcalcifications, posterior features, areolar skin thickness, nipple inversion, vascularity, and ductal echo extending from the lesion (defined as the presence of abnormal band-shaped hypoechoic ducts between the lesion and the nipple).

SE images were assessed using the 5-point elasticity scoring system established by Itoh et al. (17). According to this scale, a score of 1 was assigned when the entire lesion appeared green; a score of 2 indicated a lesion with mixed blue and green coloration; a score of 3 was given when the lesion displayed a blue center; a score of 4 corresponded to an entirely blue lesion; and a score of 5 was assigned when both the lesion and the surrounding tissue appeared blue. After scoring, the measurement software of strain rate ratio of elastography was used. The region of interest (ROI) was respectively placed in the lesion, surrounding gland tissues, adjacent fat tissue, and nipple. The strain value was recorded three times for each location, yielding the mean elastography strain value of the lesion (Em-lesion), gland (Em-gland), fat (Em-fat), and nipple (Em-nipple). Then, the lesion-to-gland strain ratio (LGR), lesion-to-fat strain ratio (LFR), and lesion-to-nipple strain ratio (LNR) were calculated.

CEUS features were extracted through frame-by-frame playback analysis of the CEUS images. The following CEUS characteristics were recorded: CEUS tumor size, enhancement homogeneity, enhancement margin, enhancement shape, enhancement order, perfusion defects, enhancement scope, perforator vessels, DEEN, and focal nipple enhancement (FNE). DEEN was defined as ductal enhancement extending from the tumor to the nipple. FNE was defined as focal enhancement in the nipple.

Pathologic evaluation

Pathological evaluation of NAC involvement was performed by an experienced pathologist. When the NAC was surgically removed by total mastectomy, skin-sparing mastectomy, or central lumpectomy, the NAC specimens were assessed according to standard protocols. Specifically, the NAC was dissected from the tissue sample, sectioned vertically along the midline, and sliced at 2–3 mm intervals. Diagnosis was based on hematoxylin and eosin staining and immunohistochemical staining. In cases where the NAC was preserved (e.g., NSM or central lumpectomy without imaging suspicion of involvement), intraoperative histological evaluation was performed on frozen sections of the retroareolar margin. Pathological findings of ductal carcinoma in situ, lobular carcinoma, invasive ductal carcinoma, lymphovascular invasion, or Paget’s disease were classified as positive for NAC involvement; benign lesions such as intraductal papilloma, atypical hyperplasia, or mastopathy were deemed NAC without involvement.

Statistical analysis

The data were analyzed using Empower (R) (X&Y Solutions, Inc., Boston, MA, USA), R software (version 4.0, http://www.empowerstats.net/analysis/index4.php), and SPSS 22.0 software (IBM Corp., Armonk, NY, USA). The normality of continuous variables was examined by the Shapiro-Wilk test. Data following a normal distribution are reported as mean ± standard deviation (SD), whereas non-normally distributed data are summarized as median (25th–75th percentiles). Categorical variables are reported as counts and percentages. Univariate analysis between groups were evaluated with independent-samples t-tests or Mann-Whitney U tests for continuous variables, and chi-square or McNemar tests for categorical variables. Least absolute shrinkage and selection operator (LASSO) logistic regression was employed to identify the independent risk factors among CUS, SE, and CEUS features associated with NAC involvement. Receiver operating characteristic (ROC) curves were generated for each predictive model based on the independent risk factors. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and AUC were calculated, and the statistical significance of differences in AUC was evaluated using the Delong test. A multi-parametric ultrasonography nomogram integrating CUS, SE, and CEUS features was developed based on the selected predictors. Internal validation was carried out via 500 bootstrap resamples; calibration curve analysis assessed predictive accuracy, and decision curve analysis (DCA) evaluated clinical utility. Statistical significance was defined as a two-sided P value of less than 0.05.

Results

Clinicopathologic information of enrolled patients

A total of 166 lesions (from 164 patients) met the inclusion criteria and were analyzed (Figure 1). All participants were female with the median age of 50 years (range, 28–82 years). According to the pathological results, approximately 19.87% (33/166) of the patients had confirmed NAC with involvement and 80.12% (133/166) patients were NAC with non-involvement. Comparison of clinical characteristics revealed a statistically significant difference in the prevalence of nipple discharge between patients with and without pathological NAC involvement (P<0.05, Table 1). However, no significant differences were observed between the two groups regarding age, menopausal status, palpable mass, or pain (all P>0.05).

Ultrasonographic features of patients with NAC involvement and non-involvement

Various CUS and SE parameters, as well as CEUS parameters, exhibited statistically significant differences between the patients with NAC involvement and non-involvement groups (Tables 2-4). On CUS, these were a shorter TND (6.5±8.5 vs. 14.0±9.8 mm; P<0.001), thicker areolar skin (3.4±0.7 vs. 3.1±0.5 mm; P=0.003), and higher percentage of nipple retraction (18.2% vs. 3.8%; P=0.003) in the patients with NAC involvement group. SE findings included higher Em-nipple (3.8±1.5 vs. 2.2±1.1; P<0.001) and a lower LNR (1.4±0.8 vs. 2.3±1.2; P<0.001). On CEUS, DEEN (84.8% vs. 16.5%; P<0.001) and FNE (75.8% vs. 12.8%; P<0.001) were the most prominent features, with peripheral claw-like enhancement also being more common (90.9% vs. 71.4%; P=0.020).

Selection of predictive features on multi-parametric ultrasonography

LASSO regression analysis selected four key predictors of NAC involvement from 35 initial sonographic features (Figure 2): ductal echo extending from the lesion on CUS, the Em-nipple value on SE, and both DEEN and FNE on CEUS. Figure 3 illustrates the representative sonographic features that were selected.

Figure 2 Feature selection using LASSO regression. (A) LASSO coefficient profiles of the sonographic features. The vertical dashed line indicates the optimal value of log(λ) selected by 10-fold cross-validation, which resulted in 4 features with nonzero coefficients. (B) Binomial deviance across log(λ) values. The vertical dashed lines correspond to the value that minimized the deviance, confirming the selection of 4 diagnostic features. LASSO, least absolute shrinkage and selection operator.

Figure 3 A 54-year-old woman with a mass located in the left upper outer quadrant of the breast, with invasive ductal carcinoma and NAC involvement confirmed by pathology. (A) Gray-scale ultrasonography demonstrated the ductal echo extending from the lesion (arrow). (B) Color Doppler revealed that the ductal echo extending from the lesion (arrow) appeared to have punctate blood flow signals. (C) SE demonstrated that the local lesion and the nipple (arrow) presented firm texture. (D) On arterial-phase CEUS, focal nipple enhancement (white arrow) and ductal enhancement extending to the nipple (yellow arrow) were detected. CEUS, contrast-enhanced ultrasound; SE, strain elastography.

Predictive efficacy and comparison of different models

Diagnostic performance for predicting NAC involvement improved with the sequential integration of sonographic modalities (Figure 4). As detailed in Table 5, the CUS + SE model demonstrated improved specificity (0.820) and a higher AUC (0.859) than CUS alone (AUC: 0.732); the combined CUS + SE + CEUS model yielded the highest diagnostic efficacy, achieving excellent sensitivity (0.909), a very high NPV (0.973), and an AUC of 0.917, with all pairwise AUC comparisons reaching statistical significance (P<0.05).

Figure 4 ROC curve of different models for predicting NAC involvement. AUC, area under the curve; CEUS, contrast-enhanced ultrasound; CUS, conventional ultrasound; NAC, nipple-areolar complex; ROC, receiver operating characteristic; SE, strain elastography.

Development, performance, and validation of the nomogram

The multi-parametric ultrasonography nomogram was constructed based on the four predictors of NAC involvement identified through LASSO regression (Figure 5). The nomogram was verified internally using 500 bootstrap samples to reduce overfitting bias. The internal validation ROC curve (Figure 6A) depicted the bootstrap 95% confidence interval (CI) for the nomogram with the AUC of 0.916. The calibration plot (Figure 6B) illustrated a good fit between the model’s predictions and the actual probabilities. The model’s decision curve (Figure 6C) charted above the “treat all” and “treat none” reference lines, indicating its robust clinical utility for predicting NAC involvement and supporting its value in preoperative decision-making.

Figure 5 Nomogram with ductal echo extending from the lesion, Em-nipple, DEEN, and FNE. DEEN, ductal enhancement extending to the nipple; Em, the mean elastography strain value; FNE, focal nipple enhancement; NAC, nipple-areolar complex.

Figure 6 Performance evaluation of the nomogram. (A) Internal validation ROC curve. The shaded blue area represented the bootstrap 95% confidence interval for the AUC. (B) Calibration plot showed good consistency between the predicted probability and the actual observed frequency. (C) DCA for the nomogram demonstrated a superior net benefit across a wide range of clinically relevant threshold probabilities. AUC, area under the curve; DCA, decision curve analysis; ROC, receiver operating characteristic.

Discussion

Driven by a heightened focus on aesthetic outcomes and quality of life post-treatment, NSM has seen broadened adoption among BC patients opting for mastectomy with reconstruction (2). Nonetheless, the oncological safety of NSM is a subject of ongoing concern, as the preserved NAC may serve as a potential reservoir for occult tumor cells (18). Therefore, prudent patient selection is imperative to ensure the oncological safety of NSM. In this study, we developed a multi-parametric ultrasonography nomogram integrating CUS, SE, and CEUS for NSM patient selection based on the ductal echo extending from the lesion, Em-nipple, DEEN, and FNE. With an AUC of 0.917, sensitivity of 90.9%, and NPV of 97.3%, this comprehensive nomogram provides reliable preoperative assessment to guide surgical planning. In our study, pathological involvement of the NAC was confirmed in 19.9% (33/166) of the original cohort. This incidence is consistent with rates reported in the literature, which typically range from 8% to 27.7% (19-21). Our analysis revealed that patients with nipple discharge were more prone to NAC involvement—a finding that aligns with the work of Billar et al., in which abnormal nipple signs or symptoms showed 61% sensitivity, 86% specificity, 45% PPV, and 92% NPV for diagnosing nipple pathology (22). Nipple discharge may result from the involvement of NAC, which occurs as cancer cells extend along the mammary ductal system toward the nipple (23).

Initial univariate analysis revealed a significant association between multiple ultrasound factors and NAC involvement, which included 2-D TND, areolar skin thickness, nipple retraction, ductal echo extending from the lesion, Em-nipple, LNR, peripheral claw-like enhancement, DEEN, and FNE. MRI features significantly correlated with NAC in previous studies (8,24-28), such as TND, nipple retraction, and thickening of the NAC, DEEN, and abnormal nipple enhancement, which are largely in line with the findings in our study. Owing to the disparity between the number of candidate ultrasound predictors and the available sample size, a penalized LASSO logistic regression model was utilized to select an optimal subset of variables most strongly linked to NAC involvement. Following feature selection, four predictors were retained: ductal echo extending from the lesion, the Em-nipple value, DEEN, and FNE. In our previous study, ductal echo extending from the lesion was classified as absent, segmental, or full course (15). As the sample size increased in this study, the frequent presentation of full course of ductal echo extending from the lesion in the NAC involvement group prompted us to dichotomize this feature into a binary variable (present or absent) for simpler recognition. Ductal echo extending from the lesion proximally along the duct may correlate with tumor invasion toward the NAC region. Our results revealed that DEEN was present in 30.1% of cases, with NAC involvement identified in 56.7% of these. A similar proportion (32.1%) of cases showing continuous enhancement from the lesion to the nipple was reported by Sakamoto et al. (26), and NAC involvement was subsequently confirmed in 62% of these cases. As for FNE, previous MRI studies have linked asymmetric nipple enhancement with occult NAC involvement. Although we did not perform contralateral CEUS evaluation of the NAC, we interpret FNE as a manifestation of asymmetric enhancement, a concept supported by its significantly higher incidence in patients with NAC involvement (75.8% vs. 12.8%). The presence of DEEN and FNE is likely due to malignant invasion, which leads to increased vessel density and permeability, thereby manifesting as hyperenhancement on CEUS. To our knowledge, this is the first study to utilize SE for nipple assessment to predict NAC involvement. Our results demonstrated that both Em-lesion and LNR differed significantly between BC patients with and without NAC involvement. Evidence indicates that tumor stiffness quantified via elastography is significantly associated with known indicators of poor prognosis, such as lymph node metastasis, lymphovascular invasion, and immunohistochemical biomarkers (12,29,30).

In our study, the combined CUS + SE + CEUS model yielded the highest diagnostic efficacy (AUC =0.917), which was superior to CUS (AUC=0.732) and CUS + SE (AUC =0.859) models. The value of this combined approach has also been demonstrated in other domains of breast research, including but not limited to differentiating benign from malignant lesions, predicting response to neoadjuvant therapy, and assessing distant metastasis (30-32). Niu et al. developed a nomogram based on a multi-parametric ultrasound approach (incorporating gray-scale, Doppler, shear-wave elastography, and CEUS) to predict ductal carcinoma in situ invasion, which achieved an AUC of 0.903 with 89.7% sensitivity, 73.8% specificity, and 84.3% overall accuracy, outperforming CUS, CUS + SWE, and CUS + CEUS (33). Another study by Liu et al. developed a nomogram integrating SE, CEUS features, and Ki-67 index, which demonstrated excellent performance (AUC =0.986) in predicting pathological complete response to neoadjuvant chemotherapy in BC patients (34). Therefore, developing comprehensive ultrasound models represents a clear and promising direction for future research in breast imaging and personalized treatment strategy formulation.

In terms of the predictive model in our study, the proposed multi-parametric ultrasonography nomogram based on the features selected by LASSO logistic regression demonstrated good discriminatory capability for predicting NAC involvement. Its performance was evidenced by an AUC of 0.916 in the primary analysis and further supported by an internally validated AUC of 0.917. Notwithstanding the existence of several high-performing preoperative predictive models (AUC =0.792–0.984) (8,35,36), most are limited to predictors from breast dynamic contrast-enhanced MRI, contrast-enhanced cone-beam breast computed tomography, clinical data, and their feature selection entails conventional univariate or multivariate regression. The nomogram was developed by integrating and linearly weighting each diagnostic factor to generate an individualized probability. This tool is designed to enable physicians to assess NAC involvement risk rapidly and accurately, thereby facilitating the identification of suitable NSM candidates. Owing to its parsimonious nature, the multi-parametric ultrasonography nomogram offers a practical and efficient diagnostic tool, particularly valuable for radiologists or clinicians with limited experience.

This study has several limitations. Its single-center design and lack of external validation may affect the generalizability of our findings. Furthermore, the limited sample size restricted more in-depth subgroup analyses. Finally, our model did not incorporate quantitative CEUS parameters, which might offer additional diagnostic insights. Based on these limitations, future research should be directed toward multicenter, large-scale prospective studies to externally validate and refine our model. Expanding the cohort will also enable robust subgroup analyses based on lesion characteristics and molecular subtypes. Moreover, integrating quantitative CEUS perfusion parameters represents a promising avenue to further enhance the model’s objectivity and predictive power.

Conclusions

The multi-parametric ultrasonography nomogram integrating CUS, SE, and CEUS demonstrates excellent diagnostic performance for predicting NAC involvement in BC patients and is particularly valuable and convenient for identifying appropriate candidates for NSM, potentially preserving cosmetic outcomes without compromising oncologic safety.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2026-1-0142/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2026-1-0142/dss

Funding: This study was supported by the Shenzhen Second People’s Hospital Clinical Research Fund of Shenzhen High-level Hospital Construction Project (Nos. 20203357001 and 2023yjlcyj003), the Shenzhen Health Economics Association Scientific Research Fund (No. 2023107), and the Shenzhen Key Medical Discipline Construction Fund (No. SZXK052).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2026-1-0142/coif). The 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. This prospective study was approved by the Ethics Committee of The First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen Second People’s Hospital (No. 20200601005), and informed consent was obtained from all patients prior to the procedure.

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/.

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